AI Engineer

Role Overview

Scope of Work

• Build AI agents and multi-agent systems using LangGraph and LangChain.
• Develop and tune prompt engineering workflows across GPT, Claude, LLaMA, and other LLMs.
• Develop REST APIs, WebSocket services, and event-driven pipelines for real-time AI services.
• Automate testing and releases through Jenkins CI/CD and maintain standards with Git, Jira, and Confluence.
• Deploy AI applications in enterprise environments using engineering best practices.
• Use Claude Code and Codex to accelerate delivery.
• Coordinate with platform, security, and product teams on scalable, secure deployments.
• Curate data layers and integrate source systems for agentic applications.

Must-Have Skills

• 3–5 years of experience in machine learning, artificial intelligence, or a related field, with production systems delivered.
• At least 1 year of experience building custom agentic AI applications.
• Strong Python skills and 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 an enterprise cloud AI platform such as Azure AI Foundry, AWS Bedrock, or Google Gemini Enterprise.
• Working knowledge of REST APIs, WebSockets, and event-driven systems.
• Proficiency with Jenkins CI/CD and Git.
• Fluency with AI-augmented development tools.
• Strong communication, analytical problem-solving, independent work, and cross-functional collaboration skills.

Good-to-Have Skills

• Familiarity with Databricks.
• Exposure to MLOps or LLMOps workflows and application monitoring.
• Knowledge of enterprise security, compliance, and governance for AI systems.
• Familiarity with code and model lifecycle management practices.