IoT Product Manager

Role Purpose & Context

Role Summary

The IoT Product Manager is responsible for managing the feature set and backlog for a specific connected device or product line. You'll spend your days translating customer problems into clear requirements for our engineering teams, making sure our IoT products actually solve real-world issues and delight users. You'll sit right at the intersection of hardware, firmware, cloud, and software, acting as the glue that holds it all together, which, honestly, is harder than it sounds. When you do this job well, our devices just work – customers love them, and we see fewer support tickets. When it's not going so well, devices might go offline, updates fail, or we build something nobody wants. The challenge? It’s constantly juggling the slow, rigid pace of hardware development with the agile demands of software, all while keeping a close eye on the bottom line. The reward? Seeing a physical product you helped create out in the wild, making a real difference to our customers.

Reporting Structure

• Reports to: Senior IoT Product Manager
• Direct reports:
• Matrix relationships: Product Owner, Connected Devices, Embedded Product Manager, Hardware Product Manager (Mid-Level), Technical Product Manager, IoT,

Key Stakeholders

Internal:

• Hardware Engineering Team
• Firmware Engineering Team
• Cloud & Software Development Teams
• Sales & Marketing Teams
• Customer Support Team
• Operations & Supply Chain

External:

• Key Customers (for feedback)
• Component Suppliers
• Connectivity Providers (e.g., cellular networks)
• Manufacturing Partners

Organisational Impact

Scope: This role directly impacts the success of our individual IoT products. Your work ensures that what we build actually meets market needs, stays competitive, and contributes to our revenue goals. Get it right, and we launch successful products; get it wrong, and we waste time and money on things nobody wants, or worse, products that fail in the field and damage our reputation.

Performance Metrics

Quantitative Metrics

1. Metric: Feature Adoption Rate
2. Desc: Percentage of active devices using a newly released feature.
3. Target: Achieve 70% adoption within 3 months of release for key features.
4. Freq: Monthly, tracked via cloud telemetry data.
5. Example: If we launch a new power-saving mode, we'd expect 70% of eligible devices to be using it within 90 days. You'd track this in our analytics dashboards.
6. Metric: Device Uptime & Connectivity
7. Desc: Overall availability and reliability of your owned devices in the field.
8. Target: Maintain 99.9% uptime for your specific product's fleet.
9. Freq: Daily/Weekly, monitored through AWS IoT Core/Azure IoT Hub logs.
10. Example: If your device fleet experiences 0.1% downtime, that's roughly 8.7 hours of outage per device per year. You'll be on top of this, spotting trends and working with engineering to fix issues.
11. Metric: Sprint Goal Completion Rate
12. Desc: Percentage of committed user stories and tasks completed within a sprint.
13. Target: Consistently achieve 85% or higher sprint goal completion.
14. Freq: Bi-weekly, reviewed during sprint retrospectives in Jira.
15. Example: If the team commits to 10 stories in a sprint, you'd aim to get 8 or 9 done. This shows you're planning well and unblocking the team effectively.
16. Metric: Support Ticket Reduction (Feature-Specific)
17. Desc: Decrease in customer support tickets directly related to your product's features post-release.
18. Target: Reduce tickets for new features by 15% quarter-over-quarter.
19. Freq: Quarterly, analysing support desk data.
20. Example: After releasing a new device provisioning flow, you'd look to see a 15% drop in 'device setup issues' tickets compared to the previous quarter. If you don't, you need to figure out why.

Qualitative Metrics

1. Metric: Cross-Functional Collaboration
2. Desc: How well you work with different teams – hardware, firmware, software, sales – to get things done.
3. Evidence: Engineering teams tell us you provide clear, actionable requirements. Sales feels you understand their customer needs. You're seen as the go-to person for questions about your product, not a blocker. You proactively bring teams together to solve problems, rather than waiting for things to blow up.
4. Metric: Product Vision & Roadmap Clarity
5. Desc: How clearly you articulate the 'what' and 'why' for your product, both internally and externally.
6. Evidence: Your product backlog is well-organised and prioritised. You can explain the next 3-6 months of development for your product to anyone, from an engineer to a sales rep, and they'll get it. People understand the problem we're solving and how your features contribute.
7. Metric: Proactive Problem Identification
8. Desc: Your ability to spot potential issues (technical, market, customer) before they become big problems.
9. Evidence: You're often the first to flag a potential component shortage, a looming firmware bug, or a shift in customer behaviour based on telemetry data. You don't just react; you anticipate. You bring solutions or options to the table, not just problems.
10. Metric: Customer Empathy & Feedback Integration
11. Desc: How effectively you understand customer pain points and translate them into product improvements.
12. Evidence: You regularly talk to customers or support teams. Your feature proposals clearly link back to customer feedback or market needs. You can articulate the 'user story' behind every major piece of work, not just the technical spec. People see you as the voice of the customer.

Primary Traits

• Trait: Systems Thinker
• Manifestation: You're the sort of person who naturally maps out the entire journey: from a sensor picking up data, through the device's firmware, over the cellular network, into our cloud, and finally, how it shows up in a customer's app. If something breaks, you're asking 'what happens if...' at every single point in that chain. You don't just see the app; you see the chip, the antenna, the battery, the network, the database, and the UI.
• Benefit: An IoT product isn't just a bit of software; it's a massively complex system. A problem could be anywhere – hardware, firmware, connectivity, cloud, or the app. If you can't see the whole picture, you'll spend ages chasing ghosts and pointing fingers at the wrong team. We need someone who can diagnose across the stack.
• Trait: Pragmatic Negotiator
• Manifestation: You can look the sales team in the eye and say, 'Look, we can't add that new sensor; the hardware board is already locked down for the next production run, and that's a 6-month delay.' But you can also convince the firmware team that adding one more tiny logging event will save our support team hundreds of hours in diagnostics. You're about finding the best path forward, even if it's not perfect, and getting everyone to buy into it.
• Benefit: You're the person stuck between the slow-moving, expensive world of hardware and the fast, agile world of software. You'll constantly be making tough trade-offs between cost, features, and shipping dates. You need to get everyone on board without burning bridges, because frankly, everyone has valid constraints.
• Trait: Resilient Problem-Solver
• Manifestation: When a customer calls up saying 1,000 devices have suddenly gone offline, you don't panic. You calmly start working with the engineering teams to figure out what's going on. Is it a bad firmware update? A network outage? A cloud service hiccup? You're methodical, you don't get flustered, and you're focused on getting things back online, whatever it takes.
• Benefit: Physical products break in ways that pure software rarely does. Supply chains snap, components fail, devices get installed incorrectly, or just get run over by a forklift. You need to have the mental fortitude to systematically troubleshoot under pressure and own the recovery plan. It's not for the faint-hearted.

Supporting Traits

• Trait: Deeply Curious
• Desc: You're genuinely interested in how things work. You'll spend your lunch break reading up on a new chipset, or trying to understand the physics behind a particular sensor. This curiosity helps you ask better questions and understand technical constraints more deeply.
• Trait: Articulate Translator
• Desc: You can take a really complex firmware bug, explain its impact to a non-technical marketing executive in plain English, and then turn around and explain the business impact of a supply chain delay to the engineering team. You bridge communication gaps effortlessly.
• Trait: Financially Literate
• Desc: You're comfortable looking at a P&L statement and can build a simple business case that scrutinises unit economics and the Bill of Materials (BOM) cost. You understand that every penny counts in hardware, and you can defend your decisions with numbers.

Primary Motivators

1. Motivator: Seeing Tangible Impact
2. Daily: You'll get a real kick out of seeing your product in customers' hands, solving their problems. It's not just code on a screen; it's a physical device doing something useful.
3. Motivator: Solving Complex, Multi-Disciplinary Puzzles
4. Daily: You thrive on the challenge of bringing together hardware, software, and cloud to create a cohesive product. It's like solving a giant, constantly evolving puzzle.
5. Motivator: Driving Innovation in a Growing Field
6. Daily: The IoT space is constantly evolving, and you'll be at the forefront, exploring new technologies and figuring out how to apply them to real products.

Potential Demotivators

Honestly, this role isn't for everyone. You'll spend a fair bit of time trying to explain to software-focused teams why a 'simple' change to the hardware isn't simple at all and requires months, not weeks. You'll deal with the constant whack-a-mole of supply chain issues, where one component finally becomes available, only for another to go out of stock. You'll also build features or even entire devices that, for various reasons (market shift, cost, technical blockers), never actually make it to production. If you need every piece of your work to ship, you'll find this frustrating.

Common Frustrations

1. The Tyranny of Hardware Timelines: Explaining for the tenth time that a 'minor' hardware tweak means a 6-month board re-spin and new regulatory certifications.
2. The 'Full-Stack' Blame Game: When a device goes offline, it's often a five-way finger-pointing match between hardware, firmware, connectivity, cloud, and the application team. You're the UN peacekeeper.
3. Supply Chain Whack-a-Mole: You finally secure that microcontroller, then the cellular module suddenly has a 52-week lead time. Your roadmap is always at the mercy of global logistics.
4. Physics is Undefeated: Dealing with real-world issues like battery degradation, RF interference in dense areas, or devices being installed in metal boxes where they shouldn't be.
5. The Long Tail of Old Firmware: Supporting customers who refuse to update, meaning you're maintaining backend compatibility for multiple firmware versions, some with known quirks.

What Role Doesn't Offer

1. A purely software-focused environment with rapid iteration cycles.
2. Complete control over every aspect of the product, especially hardware components.
3. A role where you're always building something completely new; sometimes it's about optimising existing products.
4. Predictable, routine work; expect unexpected issues with devices in the field.

ADHD Positives

1. The fast-paced, constantly changing nature of IoT problem-solving can be engaging and stimulating.
2. The need to jump between different technical domains (hardware, software, cloud) can suit those who thrive on variety.
3. The role often involves visualising complex systems, which can be a strength for many with ADHD.

ADHD Challenges and Accommodations

1. Managing multiple, often conflicting priorities and long-term hardware timelines can be challenging. We use visual roadmaps and clear prioritisation frameworks to help.
2. Documentation, while essential, can be tedious. We encourage using AI tools for drafting and provide templates to simplify the process.
3. We offer flexible working arrangements to help manage energy levels and focus, and encourage regular check-ins to re-prioritise.

Dyslexia Positives

1. Strong spatial reasoning and systems thinking, often associated with dyslexia, are highly valuable for understanding complex IoT architectures.
2. The emphasis on verbal communication and problem-solving in cross-functional meetings can be a strength.
3. Visual tools like Miro for brainstorming and diagramming are heavily used.

Dyslexia Challenges and Accommodations

1. Reading and writing extensive technical documentation (PRDs, specs) can be demanding. We use tools with dictation and text-to-speech features, and encourage visual aids.
2. Proofreading detailed requirements or release notes might require extra time. We promote peer review and AI-powered grammar checkers.
3. We can provide access to assistive technologies and offer flexible deadlines for written deliverables when needed.

Autism Positives

1. The logical, systematic nature of troubleshooting complex IoT systems can be a strong fit.
2. A preference for clear, direct communication and factual analysis is highly valued in technical product management.
3. The opportunity to deep-dive into specific technical domains (e.g., wireless protocols, sensor data) can be very rewarding.

Autism Challenges and Accommodations

1. Navigating complex social dynamics and unspoken expectations in cross-functional negotiation can be tough. We aim for direct, transparent communication and provide clear meeting agendas.
2. Unexpected changes in priorities or technical issues can be disruptive. We try to communicate changes clearly and provide as much notice as possible.
3. We offer quiet working spaces, allow for remote work when appropriate, and support the use of noise-cancelling headphones to manage sensory input.

Key Responsibilities

Experience Levels Responsibilities

1. Level: Mid-Level Professional (IoT Product Manager)
2. Responsibilities: Own the product backlog and roadmap for a specific IoT device or feature set. That means you're figuring out what needs to be built next, and why, for your area.
3. Translate high-level business goals into detailed user stories and clear technical requirements for hardware, firmware, and cloud engineering teams. Get this wrong, and they'll build the wrong thing.
4. Coordinate the full product lifecycle for your assigned device, from concept validation (is this even a good idea?) through to launch and ongoing maintenance. You'll be the go-to person.
5. Work closely with engineering teams during development, answering questions, unblocking issues, and ensuring what's being built matches the original intent. You're their first port of call.
6. Analyse device telemetry data and customer feedback to identify opportunities for product improvement or to spot potential issues. This means digging into dashboards and talking to real users.
7. Help plan and execute Over-the-Air (OTA) firmware updates, making sure we roll them out safely and effectively to avoid 'bricking' devices.
8. Collaborate with sales and marketing to develop compelling product messaging and launch materials, making sure they understand what we've built and why it matters to customers.
9. Supervision: You'll typically have weekly check-ins with your Senior Product Manager to discuss progress, roadblocks, and strategic alignment. For routine tasks, you'll work independently, but you'll escalate novel or high-risk problems for guidance. Think of it as having a safety net, but we expect you to be walking the tightrope yourself most of the time.
10. Decision: You'll have full ownership over the prioritisation of your product's backlog and the detailed feature specifications within your assigned scope. You can make routine technical decisions (e.g., specific data fields in a telemetry payload) but you'll need to consult your Senior PM on significant changes to the product roadmap, major architectural shifts, or any budget decisions over, say, £5,000 for a new component or tool. Any external commitments or public statements about the product will need approval.
11. Success: You'll know you're succeeding when your engineering teams consistently deliver features that align with your requirements, customers are happy with your product's performance, and you're seen as the expert for your specific device. Also, hitting those feature adoption and uptime targets we talked about earlier is a big one.

Decision-Making Authority

• Type: Product Backlog Prioritisation
• Entry: Suggests priorities to senior team; executes assigned tasks.
• Mid: Owns and prioritises backlog for assigned product/feature set; consults Senior PM on major shifts.
• Senior: Defines and manages roadmap for a product line; approves backlog for multiple products/features.
• Type: Technical Specification & Requirements
• Entry: Drafts requirements following templates; all reviewed by senior PM.
• Mid: Writes detailed user stories and technical requirements independently; gets sign-off from engineering leads.
• Senior: Defines architectural requirements and system interactions for new product initiatives.
• Type: Budget Allocation (for components/tools)
• Entry: None; flags needs to supervisor.
• Mid: Recommends component choices based on cost/benefit; consults Senior PM for approvals over £5K.
• Senior: Approves component selection up to £50K; manages budget for a product line.
• Type: External Communication (customer-facing)
• Entry: No direct external communication; drafts internal updates.
• Mid: Drafts release notes and FAQs; requires review and approval from Senior PM/Marketing.
• Senior: Approves external comms for product line; represents product at industry events.

Competency Requirements

Foundation Skills (Transferable)

These are the bedrock skills everyone at Zavmo needs. They're not specific to IoT, but you won't get far without them. Think of them as your professional toolkit.

• Category: Communication & Collaboration
• Skills: Active Listening: Genuinely hearing what engineers, sales, and customers are saying, not just waiting to speak.
• Clear Written Communication: Writing concise, unambiguous user stories, PRDs, and emails that leave no room for misinterpretation.
• Verbal Presentation: Explaining complex technical concepts to non-technical audiences and vice-versa, making it easy to understand.
• Conflict Resolution: Helping different teams (e.g., hardware vs. software) find common ground when priorities clash.
• Category: Problem-Solving & Critical Thinking
• Skills: Root Cause Analysis: Digging deep to find the actual source of a problem, not just patching symptoms, especially in complex IoT systems.
• Structured Thinking: Breaking down big, messy problems into smaller, manageable chunks and approaching them logically.
• Trade-off Analysis: Evaluating different options (cost, time, quality, features) and making data-backed recommendations.
• Data Interpretation: Understanding what the numbers in your dashboards actually mean and drawing actionable insights.
• Category: Adaptability & Resilience
• Skills: Managing Ambiguity: Being comfortable when things aren't perfectly clear, which happens a lot in IoT.
• Prioritisation: Constantly re-evaluating and shifting priorities as new information or issues emerge.
• Stress Tolerance: Staying calm and focused when devices go offline or a critical component is delayed.
• Learning Agility: Quickly picking up new technical concepts, tools, or market trends.

Functional Skills (Role-Specific Technical)

Now we're getting into the nitty-gritty – the specific skills and tools you'll use day-to-day to manage our IoT products. These are the practical abilities that will make you effective in this role.

Technical Competencies

• Skill: Hardware Development Lifecycle (EVT/DVT/PVT)
• Desc: Understanding the different stages of hardware development (Engineering, Design, Production Validation Testing). You'll know that hardware timelines are measured in months, not sprints, and what each 'gate' means for product readiness.
• Level: Intermediate
• Skill: OTA (Over-the-Air) Update Strategy
• Desc: You'll understand the basics of how we push firmware updates to devices in the field. This includes knowing about phased rollouts, rollback procedures, and the risks of 'bricking' devices if things go wrong. You'll help define the update process for your product.
• Level: Intermediate
• Skill: Device Fleet Management & Provisioning
• Desc: Understanding how devices get activated, authenticated, and configured when they first come online. You'll be familiar with the 'zero-touch' concept and how we manage devices throughout their lifecycle, from activation to end-of-life.
• Level: Intermediate
• Skill: Edge vs. Cloud Computing Analysis
• Desc: You can articulate the trade-offs between processing data on the device itself (edge) versus sending it to the cloud. This impacts things like latency, offline capability, battery life, and overall cost. You'll help make these decisions for your product.
• Level: Intermediate
• Skill: Data Telemetry & Schema Design
• Desc: You'll understand what 'telemetry payload' means – the specific data a device sends to the cloud. You'll help define what data points are critical, balancing the need for rich insights with constraints like battery life and cellular data costs.
• Level: Intermediate

Digital Tools

• Tool: Jira
• Level: Intermediate
• Usage: You'll use Jira daily to manage your product backlog, write clear user stories, track sprint velocity, and keep an eye on engineering progress. You'll be comfortable configuring basic workflows and filters.
• Tool: Confluence
• Level: Intermediate
• Usage: You'll create and maintain Product Requirements Documents (PRDs), meeting notes, and technical specifications in Confluence, ensuring information is organised and accessible to all teams. You'll also use it for knowledge sharing.
• Tool: AWS IoT Core / Azure IoT Hub
• Level: Intermediate
• Usage: You'll navigate the console to check device status, view basic telemetry, understand core services like Device Shadow, and debug connectivity issues. You won't be writing code, but you'll know your way around the platform.
• Tool: Tableau / Power BI / Grafana
• Level: Intermediate
• Usage: You'll build and use simple dashboards from pre-defined data sources to track device uptime, feature usage, and other key product metrics. You'll be able to pull data and create basic visualisations to share with stakeholders.
• Tool: Postman
• Level: Basic
• Usage: You'll use pre-built Postman collections to test API endpoints and verify data payloads coming from devices or going to the mobile app. It's about making sure the data flows as expected.
• Tool: Advanced Excel
• Level: Intermediate
• Usage: You'll use Excel templates to calculate basic business case ROI, Bill of Materials (BOM) costs, and track project financials. You should be comfortable with formulas, pivot tables, and basic data manipulation.

Industry Knowledge

• Area: IoT Market Trends
• Desc: A solid understanding of current trends in the IoT space, including key players, emerging technologies, and market dynamics. You'll know what's happening in the industry and how it might affect our products.
• Area: Customer Segments & Needs
• Desc: Deep knowledge of our target customer segments, their pain points, and how our IoT products solve those problems. You'll be the voice of the customer internally.

Regulatory Compliance Regulations

• Reg: CE Marking (UKCA equivalent)
• Usage: You'll understand that our hardware products need to meet certain safety and environmental standards to be sold in the UK and EU, and how this impacts product timelines and testing requirements.
• Reg: Data Protection (GDPR)
• Usage: You'll be aware of GDPR principles, especially concerning personal data collected by IoT devices, and ensure our products are designed with privacy by design in mind.

Essential Prerequisites

• Proven experience (2-5 years) in product management, ideally with some exposure to hardware or connected devices, or a strong technical background in a related field (e.g., embedded software engineering) with a desire to move into product.
• Demonstrable experience managing a product backlog and writing clear technical requirements.
• Familiarity with Agile methodologies (Scrum, Kanban) and working within engineering sprints.
• A good grasp of data analysis and using metrics to inform product decisions.
• The ability to communicate effectively with both technical and non-technical audiences.

Career Pathway Context

We're looking for someone who's already got a couple of years under their belt in product or a closely related technical discipline. You might have been an Associate Product Manager, a Business Analyst in a tech company, or even a Software Engineer who's been heavily involved in product decisions. We don't expect you to be an expert in everything, but you should have a solid foundation and be ready to take ownership of a specific product area.

Qualifications & Credentials

Emerging Foundation Skills

• Skill: Prompt Engineering & LLM Integration
• Why: Competitors are already using AI to draft reports in 10 minutes that used to take 2 hours. Product Managers who figure this out will outproduce their peers by a significant margin. This isn't just a 'nice to have' anymore; it's becoming essential for efficiency.
• Concepts: [{'concept_name': 'Context windows and token limits', 'description': "Understanding how much information an AI model can 'remember' and process at once, and how to work within those constraints."}, {'concept_name': 'Temperature settings for different tasks', 'description': 'Knowing when to ask for creative, varied output versus precise, factual responses from an LLM.'}, {'concept_name': 'RAG (Retrieval Augmented Generation) architectures', 'description': 'Learning how to connect LLMs to our internal, proprietary documentation to get accurate, context-specific answers.'}, {'concept_name': 'Output validation and hallucination detection', 'description': 'Developing a critical eye for AI-generated content, knowing when to trust it and when to double-check for inaccuracies.'}, {'concept_name': 'Prompt chaining for complex analysis', 'description': 'Breaking down large tasks into smaller, sequential prompts to guide the AI through multi-step problem-solving.'}]
• Prepare: This week: Set up GitHub Copilot or a similar AI coding assistant and use it for every piece of code or documentation you touch.
• This month: Experiment with Claude or ChatGPT to draft initial versions of user stories, acceptance criteria, or even release notes.
• Month 2: Explore how to integrate an LLM API into a simple internal tool to automate a repetitive product management task.
• Month 3: Document the time savings and quality improvements you've achieved with AI and share your findings with the team.
• QuickWin: Start using AI to summarise long emails or meeting transcripts today. No approval needed, immediate benefit. Also, use it to generate alternative headlines for your product comms – it's surprisingly good at that.

Advancing Technical Skills

• Skill: Advanced Wireless Protocol Expertise
• Why: As IoT devices become more diverse and deployed in more challenging environments, a deeper understanding of wireless communication (beyond just knowing the names) will be crucial. We'll be pushing the boundaries of what's possible with low-power, long-range communication.
• Concepts: [{'concept_name': 'RF interference mitigation techniques', 'description': 'Understanding how to design products and deployments that minimise signal disruption in crowded wireless environments.'}, {'concept_name': 'Power consumption optimisation across protocols', 'description': 'Deep-diving into how different protocols impact battery life and how to make trade-offs for specific use cases.'}, {'concept_name': 'Network topology design for large-scale deployments', 'description': 'Designing how devices communicate in complex mesh or star networks to ensure reliability and scalability.'}, {'concept_name': 'Security vulnerabilities in various wireless standards', 'description': 'Identifying and mitigating common security risks associated with different wireless communication methods.'}]
• Prepare: This quarter: Take an online course on advanced wireless communications or embedded systems networking.
• Next quarter: Work with our hardware and firmware teams to understand the specific RF challenges in our current products.
• Month 6: Research and present a comparative analysis of two emerging low-power wireless protocols (e.g., LoRaWAN vs. NB-IoT) for a future product concept.
• Month 9: Participate in a design review for a new device, specifically focusing on its wireless communication strategy.
• QuickWin: Start reading industry blogs and whitepapers on advanced wireless topics. Ask our hardware engineers about the trickiest RF problems they've faced and learn from their experience.
• Skill: Edge AI/ML Application Understanding
• Why: More and more processing will happen directly on the device, rather than in the cloud. This means better privacy, lower latency, and reduced connectivity costs. You'll need to understand the possibilities and limitations of running AI models on constrained hardware.
• Concepts: [{'concept_name': 'TinyML frameworks (e.g., TensorFlow Lite Micro)', 'description': 'Familiarity with software frameworks designed for running machine learning models on microcontrollers.'}, {'concept_name': 'Model quantisation and pruning', 'description': 'Techniques for making AI models smaller and faster so they can run efficiently on edge devices.'}, {'concept_name': 'On-device data inference vs. cloud training', 'description': 'Understanding the typical architecture where models are trained in the cloud but inferenced on the device.'}, {'concept_name': 'Power efficiency of edge AI workloads', 'description': 'Knowing how running AI on the device impacts battery life and how to make trade-offs.'}]
• Prepare: This quarter: Complete an introductory course on TinyML or embedded machine learning.
• Next quarter: Identify a potential use case for edge AI in one of our current or future products (e.g., anomaly detection on-device).
• Month 6: Work with a firmware engineer to understand the computational and memory constraints of our current device hardware.
• Month 9: Propose a small-scale pilot project to test an edge AI feature on a prototype device.
• QuickWin: Read case studies of companies successfully deploying edge AI in IoT. Brainstorm 3-5 simple 'smart' features that could run entirely on our existing devices without cloud intervention.

Education Requirements

• Level: Minimum
• Req: A Bachelor's degree in a technical field such as Computer Science, Electrical Engineering, Software Engineering, or a related discipline.
• Alts: We're pragmatic. If you don't have a degree but have 4+ years of demonstrable, relevant experience in a technical role (e.g., embedded software, systems engineering) where you were heavily involved in product decisions, we'd definitely consider it. Show us what you can do.
• Level: Preferred
• Req: A Master's degree in a relevant technical or business field (e.g., MBA with a tech focus, MSc in IoT Systems).
• Alts: Not essential, but it certainly shows a commitment to deeper learning and can accelerate your understanding of complex business or technical challenges.

Experience Requirements

You'll need roughly 2-5 years of experience in product management, or a closely related technical role (like a Technical Business Analyst, Embedded Software Engineer, or Systems Engineer) where you had significant exposure to product strategy and customer needs. We're looking for someone who has already owned a product backlog, written detailed requirements, and worked directly with engineering teams to ship features, ideally for a physical or connected product. This isn't your first rodeo, but you're still keen to learn and grow.

Preferred Certifications

• Cert: Certified Scrum Product Owner (CSPO)
• Prod: Scrum Alliance
• Usage: Shows you understand Agile principles and how to manage a product backlog effectively, which is key to working with our engineering teams.
• Cert: AWS Certified Cloud Practitioner or Azure Fundamentals
• Prod: Amazon Web Services / Microsoft Azure
• Usage: Demonstrates a foundational understanding of cloud concepts, which is crucial for managing IoT products that rely heavily on cloud backend services.
• Cert: Product Management in IoT Specialisation
• Prod: Coursera / edX (various universities)
• Usage: Specific training in IoT product management shows a focused interest and understanding of the unique challenges in this field.

Recommended Activities

• Regularly attend industry webinars and conferences focused on IoT, embedded systems, and product management to stay current with trends.
• Actively participate in online communities or forums for IoT product managers to share knowledge and learn from peers.
• Take online courses or workshops to deepen your understanding of specific technical areas like wireless protocols, cloud services, or data analytics.
• Seek out mentorship from more senior product managers within Zavmo or externally to guide your career growth.
• Read books and articles on product strategy, hardware development, and customer empathy – there's always more to learn.

Career Progression Pathways

Entry Paths to This Role

• Path: Associate IoT Product Manager
• Time: 1-2 years
• Path: Embedded Software Engineer (transition)
• Time: 2-3 years (in engineering) + 1 year (transition)
• Path: Technical Business Analyst (transition)
• Time: 2-4 years (in BA) + 1 year (transition)

Career Progression From This Role

• Pathway: Senior IoT Product Manager
• Time: 3-5 years in this role

Long Term Vision Potential Roles

• Title: Lead / Staff IoT Product Manager
• Time: 5-8 years from current role
• Title: Principal / Group Product Manager (IoT)
• Time: 8-12 years from current role
• Title: Director of Product (IoT)
• Time: 12-15 years from current role

How Zavmo Delivers This Role's Development

DISCOVER Phase: Skills Gap Analysis

Zavmo maps your current competencies against all requirements in this job description through conversational assessment. We evaluate your foundation skills (communication, strategic thinking), functional skills (CRM expertise, negotiation), and readiness for career progression.

Output: Personalised skills gap heat map showing strengths and priorities, estimated time to competency, neurodiversity accommodations.

DISCUSS Phase: Personalised Learning Pathway

Based on your DISCOVER results, Zavmo creates a personalised learning plan prioritised by impact: foundation skills first, then functional skills. We adapt to your learning style, pace, and neurodiversity needs (ADHD, dyslexia, autism).

Output: Week-by-week schedule, each module linked to specific job responsibilities, checkpoints and milestones.

DELIVER Phase: Conversational Learning

Learn through conversation, not boring modules. Zavmo uses 10 conversation types (Socratic dialogue, role-play, coaching, case studies) to build competence. Practice difficult QBR presentations, negotiate tough renewals, and handle churn conversations in a safe AI environment before facing real clients.

Example: "For 'Stakeholder Mapping', Zavmo will guide you through analysing a complex enterprise account, identifying key decision-makers, and building an engagement strategy."

DEMONSTRATE Phase: Competency Assessment

Zavmo automatically builds your evidence portfolio as you learn. Every conversation, practice scenario, and application example is captured and mapped to NOS performance criteria. When ready, your portfolio supports OFQUAL qualification claims and demonstrates competence to employers.

Output: Competency matrix, evidence portfolio (downloadable), qualification readiness, career progression score.