Role:AI Engineer(23328-1)Duration: 6-12+ Months ContractLocation – Santa Clara, CA(5 Days Onsite)Must Have SkillsSkill 1 – Lead architecture and solution design for Agentic AI applications
Skill 2 – Design and optimize AI workflows across multiple LLMs (GPT, Claude, Llama, etc.).
Skill 3 – Leverage AI-assisted development tools such as Claude Code and Codex to accelerate engineering productivity
Good To have Skills –Skill 1 – Strong expertise in Python and modern software engineering practices
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 centers 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.