Technical Product Manager

Posted 24 Days Ago
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Rīga, LVA
In-Office
60K-78K Annually
Senior level
Robotics
The Role
Lead AI-first customer-facing products for wind-energy customers by owning outcomes (adoption, engagement), running discovery, prototyping with coding agents, writing agent-executable specs, shipping small features, defining AI evals, and enabling the team to adopt AI-native workflows while partnering with commercial and operations teams.
Summary Generated by Built In

We are seeking an AI Native Technical Product Manager to lead our customer-facing software products - the Customer Platform and other tools our wind energy customers use every day. Your goal is simple to state and hard to achieve: deliver products that are actually used. You will be measured on engagement, adoption, and market value - not on features shipped or documents written. This is an AI-first product role: you will prototype with Claude Code and other coding agents, write specifications that agents can execute, build simple features yourself, and drive an agentic, specification-first development process together with our software teams. You don't need to be a career engineer - but you must be someone who builds constantly with AI, understands where AI-native product development is heading, and pulls the whole team in that direction. If you're excited to define what product management looks like when software is cheap and judgment is scarce, in a fast-growing robotics company, we encourage you to apply.
Key Responsibilities and Duties:

•         Own Product Outcomes: Define, instrument, and own the metrics that matter - user adoption, engagement, retention, and commercial value - for our customer-facing products. Success is wind farm operators using the product weekly, not a roadmap item marked done.

•         Product Strategy & Discovery: Run continuous discovery with customers (wind farm operators, OEMs, ISPs), translate insights into a clear product strategy and roadmap, and make ruthless prioritization calls under uncertainty. Create clarity in the ambiguity that rapid AI progress produces.

•         Prototype-First Validation: Turn ideas into working prototypes with AI coding agents before committing engineering capacity. Send your spec to Claude Code and see what comes back - validate UX and feasibility with clickable, working software, not slideware.

•         Agentic Development Process: Lead a specification-first, AI-augmented delivery workflow with the engineering team. Write agent-executable specs with explicit acceptance criteria, maintain the product context layer (PRDs, CLAUDE.md files, domain documentation) that makes coding agents effective, and treat every model release as a prompt to revisit what's possible.

•         Hands-on Delivery: Develop and ship simple features end-to-end using coding agents - copy changes, UI tweaks, small workflow improvements, internal tools - without blocking an engineer. Read code, review agent output, and understand the systems you manage.

•         Evals & AI Feature Quality: Define success measures and evaluation sets for AI-powered features (damage detection, analytics, agentic workflows). Ensure AI features are verified against real customer scenarios, not just demos.

•         Team Enablement: Encourage and coach the team in AI-native ways of working - shared prompt libraries, agent workflows, demos, and standards. Raise the bar for how the whole product organization uses AI.

•         Go-to-Market & Stakeholders: Partner with commercial, operations, and leadership to launch products, drive adoption inside customer accounts, and communicate strategy convincingly to both executives and engineers.


Requirements

•         Outcome Track Record: Proven experience shipping software products with measurable adoption and engagement - you can point to a product real users chose to use, and explain the metrics and decisions behind it. An outcome-over-output mindset is non-negotiable.

•         AI Tool Proficiency: Demonstrated daily use of Claude Code, Cursor, Codex, or equivalent coding agents. You can independently go from idea to working prototype, and you understand agentic workflow patterns: task decomposition, context engineering, human-in-the-loop verification.

•         Technical Fluency: You can read and reason about code (our stack is Django/Python, PostgreSQL, React), participate credibly in API and data model design discussions, and review what agents produce. You don't need to be a professional engineer - but you must be comfortable in a codebase.

•         Metrics & Analytics: Ability to define north-star and counter metrics, instrument products, query data (SQL), and turn usage data into product decisions.

•         Specification Craft: Excellent written communication - PRDs, specs, and acceptance criteria precise enough for both humans and AI agents to execute against.

•         Ambiguity & 0-1 Execution: Comfort defining product direction in ambiguous, fast-moving environments and rallying cross-functional teams around it. Bias toward action, ownership, and unblocking.

•         Continuous Learning: You follow the frontier of AI-native product development - tools, agent capabilities, and how the PM role itself is changing - and you have a clear point of view on where it is heading.

Strong Advantages:

•         Software engineering background or prior hands-on development experience

•         Experience building LLM-powered product features (evals, RAG, agents, LLM APIs)

•         Track record of transitioning a team from traditional to AI-augmented product development

•         B2B, industrial, or field-service product experience (physical assets, field operations, weather-dependent workflows)

•         Familiarity with wind energy, robotics, or industrial IoT domains


Benefits

We believe great work starts with feeling valued and supported. That’s why we are building an thoughtful, competitive benefits and perks to help you thrive — professionally and personally — through every step of your Career with us. You will be eligible for:

Salary from 5,000 EUR to 6,500 EUR per month (before Taxes)

  • A Birthday Gift
  • A modern and comfortable office location at Katlakalna iela 11E, Riga, Latvia

After Probationary Period

  • Health Insurance
  • Health Recovery Days (which can be taken as you need)
  • Paid Study Leave
  • Funding for the purchase of Vision Glasses after one (1) year of service

Join us in Building a Cleaner, Smarter Future — one quality process improvement at a time.

Skills Required

  • Proven experience shipping software products with measurable adoption and engagement
  • Daily use of Claude Code, Cursor, Codex, or equivalent coding agents
  • Ability to prototype end-to-end with coding agents and validate feasibility
  • Technical fluency to read and reason about code (Django/Python, PostgreSQL, React)
  • Ability to define metrics, instrument products, and query data (SQL) to drive decisions
  • Excellent written communication for PRDs, specs, and acceptance criteria
  • Comfort with ambiguity and 0-1 execution; bias toward action and ownership
  • Continuous learning mindset following AI-native product development and agent capabilities
  • Software engineering background or hands-on development experience
  • Experience building LLM-powered features (evals, RAG, agents, LLM APIs)
  • Track record transitioning teams to AI-augmented product development
  • B2B, industrial, or field-service product experience
  • Familiarity with wind energy, robotics, or industrial IoT
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The Company
HQ: Riga
133 Employees
Year Founded: 2018

What We Do

Aerones is an innovative company that has developed robotic technology for wind turbine blade maintenance services, such as: • Conductivity measurements and trouble-shooting; • Drainage hole cleaning; • External inspection of the wind turbine blades; • Internal inspection of the blades; • Blade & Tower cleaning; • Coating application on the leading edges; • Leading-edge repair. The technology in use is controlled remotely. In addition, it is compact and easily transportable. Aerones is the first company in the world to provide the services using robotic technology: the maintenance process does not require technicians to work in dangerous heights, and thus is much safer, more efficient, and the downtime of the turbines is decreased significantly.

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