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Senior AI Engineer
Sin especificarTiempo completoAI EngineeringEnterprise SoftwareCloud Computing
Lead the design, development, and production delivery of secure, responsible AI solutions for specialized and regulated cloud environments. Own AI architecture, reliability, evaluation, and optimization while mentoring engineers and collaborating across product, security, operations, and domain թ
Responsabilidades
- Design and build AI agents that plan, use tools and APIs, manage state and memory, and complete multi-step workflows.
- Own AI features from design through production deployment, monitoring, and live-site reliability.
- Define evaluation criteria, build datasets and automated evaluation harnesses, and coordinate human reviews where needed.
- Develop and version prompt, retrieval, memory, and tool-schema strategies.
- Analyze prompts, data, and model or tool-call traces to improve AI behavior.
- Establish quality metrics such as accuracy, groundedness, relevance, and hallucination rate, and integrate them into CI/CD release gates.
- Optimize token usage, inference cost, latency, caching, model routing, and batching.
- Implement monitoring, drift detection, user-feedback loops, and continuous improvement processes.
- Partner with product, design, security, operations, and domain stakeholders on use cases, acceptance criteria, and rollout plans.
- Provide technical leadership, influence platform direction, and mentor engineers.
Requisitos
- At least 7 years of professional software development experience, including at least 4 years building and shipping production AI or machine learning solutions.
- Proven experience building AI agents.
- Hands-on experience with AI evaluation methodologies and delivery guardrails.
- Proficiency in Python and/or C#, REST APIs, and SDKs.
- Deep knowledge of AI system design, machine learning fundamentals, generative AI, and cloud-native architectures.
- Strong prompt, retrieval, tool-schema, and model-behavior debugging skills.
- Ability to design reliable systems around probabilistic outputs.
- Strong software engineering fundamentals, including APIs, data structures, CI/CD, and observability.
Se valora
- Bachelor’s degree in computer science, engineering, or equivalent practical experience.
- Production experience with AI features on Azure.
- Experience with LLM observability, tracing, evaluation tooling, and quality gates.
- Experience with retrieval systems, indexing, chunking, reranking, and grounding.
- Experience optimizing inference cost and latency in real-time systems.
- Experience applying responsible AI practices, output governance, monitoring, and guardrails.
- Experience launching new initiatives from the ground up.