AI Engineer

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