

Nityo Infotech
Sr Gen AI Lead
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr Gen AI Lead with a contract length of "X months" and a pay rate of "$X/hour." It requires strong Python skills, LLM experience, and familiarity with LangChain and cloud AI services. Remote work location.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
Unknown
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ποΈ - Date
April 30, 2026
π - Duration
Unknown
-
ποΈ - Location
Unknown
-
π - Contract
Unknown
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π - Security
Unknown
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π - Location detailed
San Jose, CA
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π§ - Skills detailed
#Regression #Python #AI (Artificial Intelligence) #Cloud #Langchain
Role description
GenAI Engineers build the core intelligence layerβagents, workflows, prompts, and decision logicβthat power enterprise AI applications.
Technology Stack (Priority Order)
1. Languages: Python
1. Agent & RAG Frameworks: LangChain, LlamaIndex, DSPy
1. LLM APIs: Gemini, Bedrock, Vertex AI, Claude
1. Vector DBs: Pinecone, Weaviate (Can be any )
1. Evaluation: LangSmith, custom eval pipelines
Key Responsibilities
Β· Build multi-step and multi-agent workflows
Β· Implement RAG pipelines and document retrieval strategies
Β· Design prompt templates, system instructions, and guardrails
Β· Integrate agents with tools, APIs, and internal services
Β· Optimize latency, accuracy, and token usage
Β· Create automated LLM evaluation and regression tests
Required Skills
Β· Strong Python development skills
Β· Hands-on experience with LLMs and embeddings
Β· Solid understanding of prompt engineering and hallucination mitigation
Β· Familiarity with cloud AI services
GenAI Engineers build the core intelligence layerβagents, workflows, prompts, and decision logicβthat power enterprise AI applications.
Technology Stack (Priority Order)
1. Languages: Python
1. Agent & RAG Frameworks: LangChain, LlamaIndex, DSPy
1. LLM APIs: Gemini, Bedrock, Vertex AI, Claude
1. Vector DBs: Pinecone, Weaviate (Can be any )
1. Evaluation: LangSmith, custom eval pipelines
Key Responsibilities
Β· Build multi-step and multi-agent workflows
Β· Implement RAG pipelines and document retrieval strategies
Β· Design prompt templates, system instructions, and guardrails
Β· Integrate agents with tools, APIs, and internal services
Β· Optimize latency, accuracy, and token usage
Β· Create automated LLM evaluation and regression tests
Required Skills
Β· Strong Python development skills
Β· Hands-on experience with LLMs and embeddings
Β· Solid understanding of prompt engineering and hallucination mitigation
Β· Familiarity with cloud AI services






