Founding Product Engineering Manager

About Ignizia

The promise of AI is not simply to automate more work. It is to create better organizations, better work, and measurable business value.

Realizing that promise requires organizations to invest in AI where it can improve outcomes and rethink how work is done: how decisions are made, how responsibilities are shared, and how people, AI agents, and machines work together. Most importantly, organizations must make this transition with their workforce, not to it.

That is why Ignizia exists. Ignizia is the operating layer for human-AI-machine coordination. We are building toward the promise of Industry 5.0: a future that goes beyond automation to become more human-centric, resilient, and sustainable. Our mission is to make collaboration work between people, machines, and AI.

We capture and shape how an organization actually works and turn it into a living operating model that leaders and workers can redesign together. Ignizia helps organizations identify where AI will deliver measurable ROI, determine which responsibilities belong with people, agents, or machines, and prepare their workforce for how roles and skills will evolve.

Role Description

We are hiring Ignizia’s first senior engineering leader. You will be accountable for turning the product vision and existing technical foundation into a production-ready platform while building and leading the engineering team required to deliver it.

This is a hands-on player-coach role. You will manage the engineering team, own the system architecture and engineering roadmap, and continue to design and build critical parts of the product yourself.

You will also own the product-engineering quality bar. Ignizia represents complex relationships among people, workflows, decisions, AI agents, and machines. Making that complexity understandable requires excellent engineering as well as strong product, user-experience, and design judgment.

What you will own

• Hire, manage, and mentor the engineering team, with clear responsibilities, high technical standards, and direct accountability.
• Translate product priorities into an executable technical roadmap and a consistent rhythm of shipping, testing, and learning.
• Own the architecture across the web application, organizational data model, agentic AI systems, integrations, security, and infrastructure.
• Remain hands-on by designing systems, reviewing code, building critical capabilities, and resolving the hardest technical problems.
• Set the quality bar across user experience, interaction design, accessibility, performance, reliability, and design-system consistency.
• Ensure that complex organizational and AI concepts are translated into clear, intuitive experiences for leaders and workers.
• Establish engineering practices for code quality, automated testing, CI/CD, observability, incident response, and production operations.
• Establish production standards for AI evaluation, reliability, groundedness, privacy, security, latency, and cost.
• Ensure that agentic systems are grounded in organizational context, supported by evidence, and designed with appropriate human review.
• Build an engineering culture defined by ownership, intellectual honesty, urgency, and respect for the people whose work our product will affect.

Core qualifications

• Experience architecting and shipping a zero-to-one, production-grade B2B software product, ideally in an early-stage environment.
• Experience managing a small engineering team while remaining a strong individual technical contributor.
• Strong hands-on engineering ability across TypeScript and Python, with deep proficiency in at least one and the ability to review, debug, and make architectural decisions in both.
• Experience with React or Next.js, Node.js, SQL and PostgreSQL, typed Python services, asynchronous processing, and containerized cloud infrastructure.
• Experience designing relational data models, APIs, background jobs, event-driven workflows, third-party integrations, and multi-tenant application architecture.
• Direct experience shipping products built with LLMs or agentic AI, not only experimenting with models.
• Technical depth in agent orchestration, tool calling, structured outputs, context engineering, retrieval, agent state, durable execution, evaluation, tracing, and human-in-the-loop design.
• Experience establishing automated testing, CI/CD, logging, metrics, tracing, error monitoring, and production-debugging practices.
• Strong judgment about LLM failure modes, including hallucination, prompt injection, unsafe tool use, data leakage, uncertainty, model drift, latency, and cost.
• Strong product and design judgment, including the ability to evaluate interaction flows, information architecture, design-system implementation, and usability.
• The ability to move between product decisions, user experience, system architecture, implementation details, and people leadership.
• Clear communication and the confidence to challenge assumptions while remaining deeply collaborative.

Especially valuable

• Experience building software for manufacturing, supply chain, logistics, or industrial operations.
• Familiarity with ERP, MES, WMS, PLM, QMS, SCM, industrial IoT, or related operational systems.
• Experience integrating fragmented enterprise systems and translating messy operational data into a consistent domain model.
• Experience with Supabase, row-level security, workflow engines, knowledge graphs, data lineage, vector or hybrid retrieval, or systems that represent complex organizational relationships.
• Interest in organizational design, workforce transformation, Industry 5.0, and the future of human-AI collaboration.

Why join

• Work on a problem that will shape how organizations and people experience the AI transition.
• Have meaningful influence over the product, architecture, engineering team, and company.
• Receive meaningful founding equity reflecting the scope of your contribution.

This is more than an opportunity to build another AI product. It is an opportunity to help define how work will be done for decades to come.

To apply: Send your resume and a short, two-minute video explaining why this problem matters to you to ignizia@ignizia.ai.