Senior GenAI Engineer

Role Overview We are seeking a Senior GenAI Engineer with 5–7 years of experience who has independently built and deployed scalable GenAI systems. You will play a critical role in designing robust architectures and owning end-to-end delivery of production-grade AI applications.

Key Responsibilities

Design and implement scalable GenAI and RAG-based architectures Lead development using Lang. Chain / Lang. Graph and advanced orchestration techniques Architect and optimize vector search systems and embedding pipelines Develop and deploy APIs and microservices for GenAI applications Take ownership of end-to-end lifecycle : design, development, testing, deployment, monitoring Optimize performance, latency, and cost of LLM-based systems Mentor junior engineers and contribute to best practices Collaborate with product and business teams to translate requirements into AI solutions Required Skills Strong expertise in Python and backend development Deep understanding of RAG pipelines and LLM architectures Hands-on experience with Lang.

Chain / Lang. Graph Strong experience with Vector Databases (Pinecone, Weaviate, FAISS, etc.) Proven experience deploying applications on cloud platforms (AWS/GCP/Azure) Experience with Docker, Kubernetes, CI/CD pipelines Solid understanding of system design and scalability Preferred Qualifications Experience building enterprise-grade GenAI applications in production Familiarity with LLMOps / MLOps practices Exposure to multi-agent systems Experience with monitoring tools and observability