Posted on: 28/05/2026
Description :
Key Responsibilities :
- Engage Customers : Partner with client architects and executives to translate business goals into scalable GenAI use cases.
- Design Architectures : Lead design of RAG pipelines, agentic workflows, and AI copilots using LangChain / LlamaIndex, OpenAI / Azure OpenAI, and Databricks.
- Hands-on Leadership : Develop prototypes and proof-of-concepts; guide a team of AI and data engineers to productionize solutions.
- Integration : Connect LLM workflows with enterprise APIs (.NET, Power Platform, web microservices) and vector databases (FAISS, Pinecone, Qdrant).
- Governance & Communication : Drive technical documentation, estimation, and risk discussions; confidently present to senior business stakeholders.
Must-Have Skills :
- 10- 14 years in software / AI engineering, including 3+ years of LLM or applied GenAI development.
- Deep hands-on expertise with Python, LangChain/LlamaIndex, vector DBs, and OpenAI/Azure OpenAI APIs.
- Strong Azure foundation Cognitive Services, Databricks, Synapse, AI Studio, or equivalent cloud stacks.
- Experience leading RAG and agentic AI solutions from design through delivery.
- Solid grounding in prompt engineering, context optimization, and AI evaluation.
- Excellent communication can explain AI design decisions to CXO and technical audiences alike.
- Proven team leadership experience across data, ML, and application engineering.
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