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Senior, niche GenAI/LLM specialist skills reduce applicant density despite metro location.
Role requires specialized GenAI/LLM and vector DB expertise, limiting cross-industry transferability.
Explicit 7-12 years plus mandatory LLM, vector DB, and orchestration framework experience.
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Design and build generative AI/agentic systems including chat copilots, workflow/graph agents, incorporating components like chunking, hybrid search, vector stores, re-ranking, and data quality feedback loops.
Select, integrate, fine-tune, and monitor large language models (LLMs) and multimodal models, addressing hallucinations and ensuring guardrails and PII redaction.
Collaborate with presales and customer teams to build AI/ML solutions using Python, AWS services (Amazon Bedrock AgentCore, AWS QuickSuite), and agent orchestration frameworks (LangChain, Semantic Kernel, etc.).
7 to 12 years of relevant work experience in AI/ML system design and implementation.
Strong Python programming skills with experience in GenAI/AI-ML solutions.
Hands-on experience with Amazon Bedrock AgentCore, AWS QuickSuite, AWS Transform, and Kiro.
Experience with LLMs, NLP, deep learning, vector databases (Pinecone, Milvus, Redis/pgvector), hybrid search, and evaluation/observability.
Proven expertise in building and fine-tuning agentic AI systems using leading orchestration frameworks and vector databases.
Experience working in collaborative environments involving presales and client engagement for technical solution delivery.
Strong operational knowledge of CI/CD pipelines, model monitoring, guardrails configuration, and emerging GenAI advancements to optimize solutions.