Skills highlighted in blue are preferred key skills
Evaluate responses using test scenarios, quality metrics and failure cases. Tune latency, token consumption, context handling and inference reliability. Work with product and backend teams to refine requirements and integration contracts. Document experiments, safeguards and deployment decisions. Bring strong python skills and hands-on llm application experience. Design prompt chains, retrieval flows, agents and structured-output pipelines. Connect ai services with apis, databases and enterprise applications.
Opportunity for a AI Automation Engineer to contribute to a growing technology, analytics, enterprise applications, or sales function.
Client Company