GEN AI LEAD/ AI ARCHITECT

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

Contract W2

Contract Independent

Travel Required

On-site

Depends on Experience

Fitment

Dice Job Match Score™

🔗 Matching skills to job...

Job Details

Skills

Artificial Intelligence
Autogen
Confluence
Data Governance
Data Science
Database
Document Processing
Evaluation
JIRA
LangChain
Lifecycle Management
Machine Learning (ML)
Microsoft Azure
Microsoft SharePoint
Optimization
Python
Regulatory Compliance
Semantics
ServiceNow
Software Development Methodology
Software Engineering
Splunk
Test Cases
Vector Databases
Windows PowerShell
Workflow
AI-Driven
LLM
SDLC WORKFLOWS
RAG Pipelines
Open AI

Summary

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: 8920769
Posted 1 day ago

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