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Specialized GenAI senior role reduces applicant pool despite metro locations and strong LLM demand.
GenAI skills broadly transferable, but agentic frameworks and enterprise integrations add moderate domain specificity.
Multiple mandatory technical requirements including 8+ years, production GenAI experience, Python/FastAPI, LLMs, and cloud.
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Design and deploy production-grade Generative AI and Agentic AI solutions leveraging LLMs like OpenAI and Anthropic.
Build and maintain multi-agent systems including RAG pipelines, HITL workflows, and AI agent orchestration using frameworks such as LangChain and AutoGen.
Develop scalable APIs and services with Python/FastAPI, handle vector databases, and deploy on cloud platforms (Azure/AWS/GCP) with secure enterprise integrations.
8+ years of software engineering experience with strong GenAI/Agentic AI delivery background.
Proven experience deploying production AI solutions, not limited to prototypes or POCs.
Proficient in Python and FastAPI, with hands-on experience in LLMs, RAG, vector databases (FAISS, Pinecone, pgvector), and agentic AI frameworks.
Experience working with Azure or equivalent public cloud platforms (AWS/GCP) including credential management and RBAC.
Experienced in architecting and operating multi-agent AI systems integrating advanced workflows like HITL and guardrails.
Capable of making architectural decisions balancing deterministic logic and LLM-driven judgment under enterprise constraints.
Comfortable working in complex AI ecosystems involving vector DBs, cloud services, and platform integrations such as Microsoft Graph API and Salesforce.