Product Engineer (Founding Team)

You will own the technical direction and execution of the AI-Q Platform. You will lead engineering across our US and India teams, define the architecture, ship our AI agents and risk intelligence systems, harden the platform's security posture, and represent the platform technically to customers, partners, investors, and the Board. This is a founding-team role with the scope and equity to match.

• Product and engineering leadership. Co-lead the full product development lifecycle for the AI-Q Platform. Define the roadmap, set priorities, run sprints, manage releases, and ship on time across all product surfaces.
• Technical architecture and platform strategy. Define and evolve the architecture of the AI-Q Platform and the AI-Q Methodology, including data infrastructure, scoring engines, framework mapping logic, and integration patterns across vendor and buyer personas.
• AI systems and agentic capabilities. Lead the design, development, and deployment of the platform's AI agents and machine learning systems, including current and future agentic capabilities on the product roadmap.
• Risk intelligence infrastructure. Oversee the development and continuous evolution of the Living Risk Taxonomy, the AI risk data pipeline, and the vendor attestation pipeline that power platform assessments.
• Engineering team leadership. Build, manage, and develop the engineering organization, including direct hires, embedded partner teams, and contractors. Establish engineering standards, development processes, and team culture.
• Strategic and customer-facing technical representation. Serve as the senior technical voice with customers, strategic partners, investors, and the Board on platform, technology, and methodology matters.

• 2 to 4 years of full-stack engineering experience, or a recent CS or AI graduate with strong shipping experience from internships, research, or independent work.
• AI-native. You have built with LLMs in production, you use AI coding agents as a daily practice, and you have informed opinions on where models accelerate teams and where they fail.
• Strong critical thinker. You challenge requirements before writing code, ask what a feature is solving, and bring a point of view to architectural decisions.
• Customer-credible. You can hold a technical conversation with a CISO, a head of compliance, or a Board member and adjust your register for each audience.
• Comfortable with high scope and ambiguity. You read the responsibilities above and felt energized rather than overwhelmed.

• Experience building on modern AI APIs, agent frameworks and data retrieval concepts (RAG, Vector Databases, embeddings, etc.)
• Understanding of strong computer system designs for scalable cloud based architecture (AWS, GCP, Azure)
• Production experience in a regulated industry such as healthcare, financial services, government, or defense.
• Experience leading or collaborating with offshore engineering teams.
• A body of public work, including GitHub, technical writing, research, or talks.

• Founding-team scope and equity at a company shipping into real, regulated customer environments.
• Direct ownership of the technical roadmap, architecture, and team structure from day one.
• A working relationship with senior advisors across AI, security, healthcare technology, and enterprise sales.
• A career trajectory that compresses a decade of typical engineering progression into a few years for the right operator.