End-to-End Product Ownership: Translate business goals into working, deployable systems
Define architecture, workflows, and implementation plans
Ship and maintain production-grade systems — not demos or prototypes
Rapid Prototyping & Iteration: Turn ambiguous ideas into working demos within hours or days
Prototype using code, AI tooling, automation, or low-code systems
Validate through experiments and real user feedback, then iterate to production quality
Build AI-Native Systems: Design and orchestrate LLM agents, retrieval pipelines, workflow automation, memory layers, APIs, and guardrails
Design for Scale, Cost & Performance: Reason through token consumption, inference cost, latency constraints, infrastructure scalability, and system resilience
Operational Excellence: Instrument systems with monitoring and telemetry
Build evaluation loops for continuous quality improvement
Automate workflows that increase engineering velocity
Maintain clear, repeatable documentation

5+ years of software engineering experience
Demonstrated track record of shipping production systems
Strong systems thinking and logical reasoning
High ownership mindset; operates well with minimal supervision
Comfortable with ambiguity and fast iteration cycles
Experience with APIs, automation tools, or AI platforms
Ability to reason about infrastructure tradeoffs and system reliability
Experience building LLM-based or AI-driven products (preferred)
Familiarity with evaluation frameworks, monitoring, or instrumentation (preferred)
Experience with data pipelines, analytics, or telemetry (preferred)
Strong UX and front-end sensibility (preferred)
Portfolio or GitHub showcasing deployed systems (preferred)

Full Stack Developer

Key skills