Hello,
Hope this mail finds you well!
We have an immediate contract opportunity with one of our clients.
Please review the details below and if you have any suitable profile please share your updated resume at
Referrals are also appreciated!
Position: Lead AI Engineer
Location: Santa Clara, CA Onsite
Experience Required: 10+ Years
Employment Type: Contract (Only W2)
Job Overview
We are seeking an experienced Lead AI Engineer to architect, lead, and deliver production-grade Agentic AI solutions for enterprise environments. The ideal candidate will have strong hands-on expertise in Python, LangGraph, LangChain, LLMs, prompt engineering, and cloud-based AI platforms, with proven experience designing scalable multi-agent systems and leading technical initiatives.
The Lead AI Engineer will work closely with engineering, platform, security, data, and product teams to define AI architecture, guide development, integrate enterprise systems, and operationalize secure and reliable AI applications.
Key Responsibilities
- Lead the architecture, technical design, and implementation of enterprise-grade Agentic AI applications.
- Design and build intelligent AI agents and multi-agent systems using LangGraph and LangChain.
- Develop complex agent workflows incorporating planning, reasoning, tool calling, memory, orchestration, and human-in-the-loop capabilities.
- Design and optimize AI workflows across multiple LLM providers, including GPT, Claude, Llama, and other foundation models.
- Evaluate LLM capabilities and select appropriate models based on performance, cost, latency, security, and business requirements.
- Develop scalable AI services and enterprise integrations using Python, REST APIs, event-driven architectures, and microservices.
- Establish software engineering standards, reusable frameworks, coding practices, and development patterns for Agentic AI solutions.
- Lead and mentor engineering teams developing AI-powered applications and services.
- Drive end-to-end solution delivery from architecture and proof of concept through production deployment and operational support.
- Integrate AI applications with enterprise data sources, APIs, applications, databases, and business systems.
- Design event-driven AI architectures using messaging, asynchronous processing, and distributed services.
- Deploy and operationalize AI applications across Azure, AWS, Google Cloud Platform, and other cloud environments.
- Leverage platforms such as Azure AI Foundry, AWS Bedrock, and Google Gemini Enterprise to build and deploy enterprise AI solutions.
- Implement CI/CD pipelines and automated deployment processes for AI applications.
- Work with platform and cloud engineering teams to ensure scalability, reliability, availability, and performance.
- Collaborate with security teams to implement secure AI architectures, access controls, data protection, and responsible AI practices.
- Partner with data teams to integrate enterprise data and enable AI applications with reliable data pipelines and contextual information.
- Leverage AI-assisted development tools such as Claude Code and Codex to accelerate development and engineering productivity.
- Establish best practices for prompt engineering, LLM integration, agent orchestration, evaluation, and production readiness.
- Troubleshoot AI application issues and optimize system performance, latency, reliability, and operational efficiency.
- Drive technical decisions, architecture reviews, design discussions, and engineering standards.
- Communicate technical solutions and architecture effectively to engineering teams, business stakeholders, and leadership.
Must-Have Skills
- 7+ years of experience in AI/ML engineering or related disciplines.
- 2+ year of hands-on experience building Agentic AI solutions.
- Strong proficiency in Python and modern software engineering practices.
- Hands-on expertise with LangGraph and LangChain.
- Strong understanding of Large Language Models (LLMs) and foundation models.
- Strong experience with prompt engineering and LLM application development.
- Experience designing and deploying enterprise AI applications.
- Experience building multi-agent AI systems and agentic workflows.
- Familiarity with one or more enterprise AI platforms:
- Azure AI Foundry
- AWS Bedrock
- Google Gemini Enterprise
- Similar enterprise AI platforms
- Strong understanding of REST APIs, microservices, event-driven architectures, and distributed systems.
- Experience with CI/CD and cloud deployment.
- Experience integrating AI applications with enterprise data and business systems.
- Proven ability to lead technical initiatives and drive solutions from architecture through production.
- Strong stakeholder management, communication, troubleshooting, and problem-solving skills.
Good-to-Have Skills
- Databricks and enterprise data platforms.
- MLOps / LLMOps.
- AI model lifecycle management and evaluation.
- Enterprise AI Governance, Security, and Responsible AI.
- AI monitoring, observability, and performance management.
- Knowledge of RAG architectures, vector databases, embeddings, and semantic search.
- Experience with AI application evaluation, guardrails, and hallucination mitigation.
- Enterprise AI architecture and technology strategy.
- Experience with Kubernetes and containerized AI workloads.
- Familiarity with model optimization, inference, cost management, and scalability.
Thanks & Regards,
Divya Chandrala
|
+1- Ext:134
Vsion Technologies, Inc.
507 Denali Pass , Suite 602 , Cedar Park , TX 78613
Certified Minority Business Enterprise ( MBE ) / Woman-Owned Business Enterprise ( WBE )
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