We are seeking a highly skilled Senior GenAI Engineer with 3–8 years of experience and a proven track record of independently building, deploying, and scaling production-grade Generative AI systems. In this role, you will take full ownership of designing robust architectures and delivering end‑to‑end GenAI applications that solve real business problems.
Key Responsibilities
- Design, architect, and implement scalable Generative AI and RAG-based solutions.
- Lead hands-on development using LangChain / LangGraph and advanced orchestration techniques.
- Architect, optimize, and maintain vector search systems and embedding pipelines.
- Build, deploy, and manage APIs and microservices supporting GenAI applications.
- Own the complete solution lifecycle, including design, development, testing, deployment, monitoring, and optimization.
- Continuously optimize performance, latency, scalability, and cost of LLM-driven systems.
- Mentor junior engineers and help establish engineering best practices and standards.
- Collaborate closely with product, business, and stakeholder teams to translate requirements into effective AI-driven solutions.
Required Skills & Qualifications
- Strong expertise in Python and backend development
- Deep understanding of LLM architectures and Retrieval-Augmented Generation (RAG) pipelines
- Hands-on experience with LangChain and/or LangGraph
- Strong experience with Vector Databases such as Pinecone, Weaviate, FAISS, or similar
- Proven experience deploying and scaling applications on cloud platforms (AWS, GCP, or Azure)
- Experience with Docker, Kubernetes, and CI/CD pipelines
- Solid foundation in system design, scalability, and distributed architectures
Preferred Qualifications
- Experience building enterprise-grade GenAI applications in production environments
- Familiarity with LLMOps / MLOps practices
- Exposure to multi-agent or agentic AI systems
- Experience with monitoring, logging, and observability tools for AI systems
