Your profile

Must haves

7+ years of professional software engineering experience, or equivalent evidence of senior/principal-level impact in production product development.

A strong record of shipping and operating customer-facing software—not only notebooks, proofs of concept, demos, or advisory work.

Professional proficiency in Python and strong ability in at least one product engineering language such as C#, TypeScript, or Java.

Hands-on experience building production LLM or agentic applications, including several of the following: retrieval and grounding, embeddings or hybrid search, structured outputs, tool or function calling, context and state management, model selection or routing, and human approval or escalation.

Experience with data-intensive systems: APIs and integrations, event or streaming data, ingestion and transformation, data quality, metadata, storage, and operational observability.

Strong system-design fundamentals for API-first, distributed, cloud-native, multi-tenant SaaS products, including identity, authorization, reliability, performance, and secure integration with enterprise systems.

Practical experience evaluating and diagnosing AI systems through datasets, traces, qualitative review, quantitative metrics, automated tests, CI/CD, and production telemetry.

Pragmatic architectural judgment. You know when conventional software is sufficient, when AI adds real value, and how to balance fast validation with a credible path to production.

Clear communication and product thinking. You can work directly with developers and customers, translate ambiguous needs into a testable technical plan, explain trade-offs, and drive an end-to-end result across team boundaries.

A degree in computer science, software engineering, AI/ML, or a related field—or equivalent practical experience.