Description

You will design and build production-ready AI agent systems and cloud-native infrastructure.

This role is on-site.

Responsibilities

• Design and implement AI agents, including RAG orchestration, tool invocation, and policy-based routing.
• Build evaluation frameworks for accuracy, latency, and reliability, and implement observability for agent lifecycles.
• Integrate with AI providers (OpenAI, Anthropic, Google Vertex) and create abstraction layers for multi-model architectures.
• Develop scalable microservices using Docker, Kubernetes, and serverless patterns with CI/CD and infrastructure as code.
• Define test strategies for AI systems, measuring performance metrics and debugging production issues.

Required Skills

• 8–10+ years of software engineering experience with a Bachelor's degree.
• Strong proficiency in Python or Java for backend development.
• Experience building and deploying AI/LLM-based systems (agents, RAG, orchestration) in production.
• Hands-on experience with cloud-native systems: APIs, microservices, containers (Docker, Kubernetes), and serverless.
• Proficiency with CI/CD pipelines and Infrastructure as Code tools (Terraform, Helm).
• Familiarity with monitoring and observability tools for production readiness.
• Experience integrating with AI platforms like OpenAI, Claude, or Vertex AI.

Preferred Skills

• Experience with agent frameworks such as LangGraph, AutoGen, or CrewAI.
• Design experience for multi-agent or distributed AI systems.

Key Skills

Education

Bachelor's degree