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 LangChain / LangGraph 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 LangChain / LangGraph
- 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
