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Tier-1 employer, metro location, and mid-level experience band increase candidate competition.
Specialized GenAI, LLM orchestration, and cloud AI tooling substantially reduce cross-industry transferability.
Explicit 4–7 year requirement plus many mandatory GenAI, cloud, and LLM tooling skills raises strictness.
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Develop and deploy enterprise-grade Generative AI applications, APIs, and microservices.
Optimize Retrieval-Augmented Generation (RAG) pipelines and build autonomous multi-agent AI workflows to automate complex business processes.
Integrate commercial and foundational AI models within cloud platforms and implement responsible AI guardrails and monitoring frameworks.
4-7 years of software development experience with strong computer science fundamentals.
Proficiency in Python programming and API development using frameworks like FastAPI, Flask, or Django.
Hands-on experience with one major cloud AI ecosystem: GCP (Vertex AI), Azure (OpenAI Service), or AWS (Bedrock).
Bachelor's degree in Engineering/Technology (BE/BTech), MTech, MCA, or MBA (full-time).
Experienced in complex GenAI system design including vector databases, prompt engineering, and embeddings.
Familiar with DevOps and LLM operations including containerization (Docker), CI/CD, and LLM monitoring tools.
Able to rapidly prototype Proof of Concepts (PoCs) demonstrating GenAI capabilities to clients and internal stakeholders.