Artificial Intelligence Engineer
Posted
Description
- 12+ years in software engineering with direct ownership of systems in production
- Agentic systems you personally built and shipped into production, not prototypes, notebooks, or proofs of concept
- Strong programming proficiency in Python and at least one of TypeScript/JavaScript, Go, or an equivalent language, with demonstrable code quality practice covering testing, review, refactoring, and maintainability
- Hands-on implementation experience across:
- Agent loops and tool calling: loop control, sub-agent delegation, state management and checkpointing, and idempotent handling of consequential actions
- Context engineering: retrieval and search, memory, grounding in enterprise data, prompt assembly, and structured or schema-constrained output
- Testing and validation: automated tests for behavior that varies between runs, regression suites, and validation against defined acceptance criteria
- Cost and latency engineering: token accounting, prompt and response caching, model routing with fallback, and context compaction
- Process re-engineering experience: analyzing an existing workflow and rebuilding it around what automation makes possible, rather than encoding current practice into software
- Experience replacing an existing manual or fragmented business process with software, working directly with the people who perform that process today
- Integration engineering: REST and GraphQL APIs, event-driven consumers, OAuth and scoped credential handling, schema and contract versioning, and resilient behavior under partial failure
- Observability and delivery engineering: structured logging, distributed tracing, and metrics for systems whose behavior varies between runs, plus CI/CD pipelines, automated quality gates, and containerized deployment
- Ability to work independently from written specification, deliver against committed timelines, and communicate progress and blockers without prompting