AI Senior Engineer

AI Senior EngineerAbout the Role:We are looking for a highly capable AI Lead Engineer to contribute to the design and delivery of intelligent, scalable AI solutions
This role focuses on building production-grade systems involving LLMs, vector databases, agent-based workflows, and Retrieval-Augmented Generation (RAG) architectures on the cloud The ideal candidate should demonstrate strong problem-solving abilities, hands-on technical skills, and the ability to align AI design with real-world business needsMust-Have Skills Strong coding ability in Python and proficiency in SQL Hands-on experience with vector databases (eg, Pinecone, FAISS, Weaviate) Practical experience with LLMs (OpenAI, Claude, Gemini, etc) in real-world workflows Familiarity with LangChain, LlamaIndex, or similar orchestration tools Proven track record in delivering scalable AI systems on public cloud (Azure, AWS, or GCP) Experience building and optimizing RAG pipelines Solid understanding of server less/cloud-native architecture and event-driven design Integrate/expose the ai solution in applications using fastapi,flask,djangoPreferred or Good to Have Skills Exposure to agentic AI patterns and multi-agent coordination Knowledge of AI system safety practices (eg, hallucination filtering, grounding) Experience with MLOps tools (MLflow, KubeFlow) and CI/CD for ML Understanding of concept/data drift and retraining strategies in production Experience working on AI projects involving classification, regression, and clustering models Prior work on multi-modal AI pipelines (vision + language) Familiarity with real-time inference tuning (batching, concurrency) Demonstrated ability to deliver a variety of AI solutions in production environments across domainsAny Other: Bachelor s or Master s degree in Computer Science, Data Science, AI/ML, or related field Strong analytical mindset with a clear focus on business-aligned AI delivery Excellent verbal and written communication skillsKey Responsibilities Collaborate with the Solution Architect to design agentic AI systems (eg, ReAct, CodeAct, Self-Reflective Agents) Build and deploy scalable RAG pipelines using vector databases and embedding models Integrate modern AI tools (eg, LangChain, LlamaIndex, Kagi, Search APIs) into solution workflows Optimize inference performance for cloud and edge environments Contribute to the development of feedback loops, drift detection, and self-healing AI systems Deploy, monitor, and manage AI solutions on cloud platforms (Azure, AWS, or GCP) Translate business use cases into robust technical solutions in collaboration with cross-functional teams