Agentic AI Engineer

You will design multi-agent systems, connect agents to internal services and infrastructure APIs, build coding and self-correcting agents, architect agent memory, implement RAG pipelines and evaluation guardrails, automate agent deployment and governance, and integrate autonomous capabilities into Kubernetes control planes.

Responsibilities

• Design and build scalable multi-agent architectures for engineering and business workflows
• Integrate AI agents with internal services, SaaS platforms, and APIs
• Automate infrastructure actions including node cordoning, checkpointing, and hardware remediation
• Develop agents that generate code, refactor software, analyze telemetry, and correct system issues
• Architect short-term and long-term agent memory using protocols such as MCP
• Implement RAG pipelines grounded in telemetry and observability data
• Enforce agent evaluation, reliability, and security guardrails with LLM-as-a-Judge mechanisms
• Establish company-wide Harness engineering practices
• Automate the deployment, governance, and lifecycle management of agentic systems
• Apply CI/CD and feature flagging to agentic systems
• Collaborate with Kubernetes and infrastructure engineers to integrate agents into the platform control plane

Requirements

• Bachelor's or master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field
• At least 6 years of software engineering experience
• Deep expertise in production-grade Python and TypeScript
• Extensive experience with agentic frameworks such as LangGraph and CrewAI
• Experience working with frontier large language models such as OpenAI and Anthropic Claude
• Experience mapping ambiguous business processes into reusable AI logic and patterns
• Experience deploying AI features into managed runtimes and cloud-native environments
• Familiarity with AWS, Azure, GCP, or private clouds
• Familiarity with Kubernetes internals, infrastructure automation, and CI/CD pipelines
• Experience with Jenkins, GitHub Actions, or Harness
• Strong understanding of distributed systems, telemetry, observability stacks, and hardware metrics
• Leadership experience connecting traditional software engineering with autonomous AI
• Excellent communication skills
• Ability to deliver scalable and reliable software in a high-velocity cross-functional environment