GenAI Sr Lead/ Associate Architect

Fremont, CA, US • Posted 1 day ago • Updated 1 day ago

Contract Corp To Corp

Contract W2

Contract Independent

On-site

Depends on Experience

Fitment

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Job Details

Skills

Artificial Intelligence
Machine Learning (ML)
ServiceNow
LangChain
Autogen
Vector Databases
Confluence

Summary

Job Title: GenAI Sr Lead/ Associate Architect
Location: Fremont, CA
Mandatory Skills: Splunk, PowerShell, or Python, ServiceNow, Jira, Logs Monitoring, Confluence and SharePoint
Experience Requirements:

10+ years of experience in software engineering, machine learning, data science, or artificial intelligence.
3+ years with LLM frameworks, evaluation tools, or observability platforms like Langfuse, LangChain, Azure AI, etc.

Qualifications:

Bachelor s or master s degree in computer science, Engineering, or a related field.

Key Skills: Splunk, PowerShell, or Python, ServiceNow, Jira, Logs Monitoring, Confluence and SharePoint
Skill Requirements: Strong Experience on Agentic frameworks (LangChain / LangGraph / Semantic Kernel / AutoGen etc.).

Handson expertise in multiagent orchestration and lifecycle management.
Proficiency with Retrieval-Augmented Generation (RAG), fine-tuning, and multi-agent orchestration.
Good understanding of advanced RAG patterns: hierarchical chunking, embedding strategies, vector DB selection, semantic filtering, context window optimization.
Strong familiarity with Vector databases, RAG pipelines, Embedding models, Retrieval strategies.
Proficiency in LLM Platforms: Azure OpenAI/OpenAI/other enterprise LLMs (with exposure LLM APIs and frameworks).
Experience integrating LLMs into enterprise SDLC workflows.
Experience in Designing multiagent systems (Document Agent, Requirement Agent, Scenario Agent, Test Case Agent, Automation Agent) with deterministic handoffs and feedback loops.
Familiarity with data governance, responsible AI practices, AI ethics, and compliance.
Experience with: Prompt layer refinement, fewshot prompting, Structured output generation, Guardrails to avoid hallucinated requirements or test steps
Experience implementing end-to-end AI-driven workflows.
Exposure to parallel document processing and largescale agent concurrency
Experience with incremental regeneration strategies
Experience building AI copilots for enterprise workflows.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 90942645
Position Id: 8920796
Posted 1 day ago

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