Lead AI/AI Engineer

Team Need quick submission here . need 2-3 resumes on each role . Try to submit locals within 50 miles

We are looking for AI Engineer and Lead AI Engineer profiles. Please share your best matching candidates along with their resume, at the earliest.

Requrement1::

Lead AI Engineer

Santa Clara, CA Submit locals within 50 Miles

Rate :: 70-75/hr on C2C

5 Days onsite

Lead AI Engineer to architect, lead, and deliver production-grade Agentic AI solutions for enterprise use.

The individual will drive solution design, guide development teams, build multi-agent AI systems, and ensure scalable, secure, and reliable deployment in production environments.

Scope of Work

Lead architecture and solution design for Agentic AI applications.

Build and oversee development of AI agents and multi-agent systems using LangGraph and LangChain.

Design and optimize AI workflows across multiple LLMs (GPT, Claude, Llama, etc.).

Guide engineering teams and establish development best practices.

Develop enterprise integrations, APIs, and event-driven AI services.

Drive deployment, operationalization, and scalability of AI applications.

Coordinate with platform, security, data, and product teams to ensure successful delivery.

Leverage AI-assisted development tools such as Claude Code and Codex to accelerate engineering productivity.

Must-Have Skills

5+ years of experience in AI/ML.

1+ years of experience building Agentic AI solutions.

Strong expertise in Python and modern software engineering practices.

Hands-on experience with LangGraph, LangChain, LLMs, and prompt engineering.

Experience architecting and deploying enterprise AI applications.

Familiarity with Azure AI Foundry, AWS Bedrock, Google Gemini Enterprise, or similar platforms.

Strong understanding of APIs, event-driven architectures, CI/CD, and cloud deployment.

Proven ability to lead technical initiatives and drive solution delivery.

Excellent communication, stakeholder management, and problem-solving skills.

Experience with enterprise data integration and AI application deployment.

Good-to-Have Skills

Databricks

MLOps / LLMOps

Enterprise AI Governance and Security

AI Monitoring and Observability

Enterprise AI Architecture and Strategy

Requirement1::

AI Engineer

Santa Clara, CA Submit locals within 50 Miles

Rate :: 65-70/hr on C2C

5 Days onsite

• AI Engineer to build and deliver production-grade agentic AI systems for enterprise use.
• The engineer will develop multi-agent workflows, integrate large language models into existing enterprise systems, and support the deployment and automation needed to run them reliably and securely in production.
• This is a hands-on engineering engagement.
• The work centres on building agents, orchestration logic, and supporting infrastructure that performs under real production workloads, not on proof-of-concept or advisory work.

Scope of Work

Build AI agents and multi-agent systems using frameworks with LangGraph and LangChain tools.

Develop and tune prompt engineering workflows across multiple LLMs (GPT, Claude, LLaMA), balancing reliability, cost, and latency.

Develop REST APIs, WebSocket services, and event-driven pipelines for real-time AI services that remain stable under load.

Automate testing and releases through Jenkins CI/CD, and maintain code and documentation standards using Git, Jira, and Confluence.

Deployment of AI Application in enterprise adhering to best practices

Use AI-augmented development tools such as Claude Code and Codex to accelerate delivery.

Coordinate with platform, security, and product teams to deliver scalable, secure deployments.

Must-Have Skills

3-5 years in Machine Learning, AI, or a related field, with production systems delivered.

At least 1 year building custom Agentic AI applications

Strong Python skills and sound modern development practices.

Hands-on experience with LLMs and prompt engineering across the full application lifecycle.

Demonstrated experience building AI agents with LangGraph.

Familiarity with at least one enterprise cloud AI platform for building and deploying agentic applications, such as Azure AI Foundry, AWS Bedrock, or Google Gemini Enterprise,

including cloud-native deployment practices.

Working knowledge of REST APIs, WebSockets, and event-driven systems.

Proficiency with CI/CD tooling (Jenkins) and version control (Git).

Fluency with AI-augmented development tools for rapid prototyping.

Strong written and verbal communication, an analytical approach to problem-solving, and the ability to work independently within a cross-functional team.

Data layer curations and integration with source system for agentic application

Good-to-Have Skills

Familiarity with Databricks.

Exposure to MLOps/LLMOps workflows and application monitoring.

Knowledge of enterprise security, compliance, and governance for AI systems.

Familiarity with code and model lifecycle management practices.