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Senior ML/GenAI role, metro location, broad skillset, and known enterprise brand increase competition.
Highly domain-specific ML/GenAI skills and LangChain/multimodal experience reduce cross-industry transferability.
Explicit 6+ years, specialized GenAI stack, cloud and SRE requirements make filters strict.
Lead architecture and delivery of cloud micro-services using Python and AI frameworks (e.g., LangChain, FastAPI).
Own end-to-end GenAI initiatives including data strategy, model fine-tuning, deployment, and continuous optimization for advanced AI capabilities (structured reasoning, autonomous planning, image/video generation).
Set engineering standards (reliability, security, CI/CD), drive cross-functional execution, mentor engineers, and lead production excellence including incident response and root cause analyses.
Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience; Master’s preferred.
6+ years of professional Python development experience, including large-scale production AI/ML systems.
Hands-on cloud experience with GCP, AWS, or Azure; containerization with Docker and Kubernetes; and CI/CD pipeline expertise.
Demonstrated leadership in technical direction setting and mentoring engineers.
Deep expertise in AI/GenAI frameworks such as LangChain, LangGraph and multimodal model orchestration tools (ADK, MCP, A2A).
Experience working with cloud AI services (Vertex AI, BigQuery, GKE, Kubeflow) and modern DevOps tooling (Terraform, GitHub Actions, Kubernetes).
Proven ability to own complex AI product features end-to-end in a high-impact, customer-focused, and ambiguous environment with strong emphasis on production readiness and engineering rigor.