Staff Generative AI Engineer specializing in Generative and Agentic AI applications. Developing scalable AI systems and mentoring engineering talent.
Responsibilities
Design, build, and ship production-grade Generative and Agentic AI applications and services for internal and external users
Develop high-quality backend services in Python, with strong software engineering rigor around testing, performance, and maintainability
Champion reusability and abstraction in everything you build by designing and building modular, well-abstracted components and libraries
Build multi-agent systems using frameworks such as LangChain, LangGraph, Claude Agent SDK and Google ADK
Integrate with leading LLM and foundation model APIs, including Azure OpenAI, Google Vertex AI, and AWS Bedrock
Design and implement Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking strategies, embeddings, vector search, and re-ranking
Build clean, well-tested RESTful and/or gRPC APIs with a strong focus on reliability, security, and performance
Implement observability, tracing, evaluation, guardrails for Generative and Agentic AI applications
Deploy and operate services on major cloud providers (e.g., GCP, AWS, and Azure) leveraging managed services
Contribute to platform architecture decisions and engineering best practices
Take applications from prototype through production deployment, hardening, and ongoing operation
Mentor and coach junior and mid-level engineers through code reviews, architecture discussions, and pair programming
Foster a culture of engineering excellence, knowledge sharing, and continuous improvement
Participate in technical design reviews and contribute to the professional growth of team members
Requirements
10-15 years of professional software engineering experience with at least 3-5 years of experience building AI/ML software products
Bachelor’s degree in Computer Science or a related field (Master’s degree preferred)
Strong proficiency in Python, with deep software engineering fundamentals (abstraction, modularity, system design, testing, performance)
Hands-on experience building and shipping Generative and Agentic AI applications, including LLM integration, prompt engineering, and/or agentic workflows
Practical experience integrating cloud-hosted LLM APIs such as Azure OpenAI, Vertex AI, and/or AWS Bedrock
Experience with agent frameworks (e.g., LangChain, LangGraph, Google ADK, Claude Agent SDK) and vector databases (e.g., Pinecone, Weaviate, pgvector, Open Search, AlloyDB)
Hands-on experience with Google Cloud Platform (GCP), Amazon Web Services (AWS), or Azure
Strong understanding of API design, distributed systems, and cloud-native architecture
Proven track record of taking systems from design through production deployment and operation
Experience with containerization and orchestration (Docker, Kubernetes)
Knowledge of Generative AI Risk Management frameworks (NIST RFM)
Experience supporting developer platforms or internal tooling
Experience writing design documents or helping define engineering standards
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