Description

Key Skills: Agentic AI, AI/ML, AI Artificial intelligence, Generative AI, Python

Roles and Responsibilities:

• Own the architecture and engineering of applied AI platform components, including services, pipelines, integrations, and infrastructure for production model delivery.
• Design and build production services and APIs (FastAPI and MCP servers) that expose AI capabilities to internal applications and downstream systems.
• Build and operate Databricks pipelines and workflows for production ML and LLM systems with strong testing, code quality, and reproducibility.
• Engineer production LLM applications using RAG, agentic workflows, tool use, eval harnesses, and prompt management while managing latency, cost, and safety trade-offs.
• Establish and uphold MLOps standards including CI/CD for models, deployment automation, monitoring, drift detection, observability, alerting, and incident response.

Skills Required:

• 7+ years of software/ML engineering experience with senior-level ownership and a track record of shipping and operating production systems.
• AI / AI-ML engineering with agentic AI experience in production contexts.
• Production service development using Python and FastAPI (or equivalent service framework) with strong API design and reliability practices.
• Production data and ML pipeline experience with Databricks, PySpark, Delta Lake, MLflow, and Databricks Workflows.
• LLM application engineering and MLOps: RAG, evals, prompt management, latency/cost/safety engineering, and production monitoring/observability with CI/CD.

Good to Have:

• Generative AI experience.

Education: Bachelor's degree in Computer Science, Software Engineering, or a related technical field (or equivalent work experience)

Key Skills

Education

Any Graduate