AI Engineer (Agentic/Applied)

You build production agentic architectures running inside real client organizations, not demos or prototypes. As an AI Engineer (Agentic/Applied), you will design, build and deploy production-grade agentic AI systems across the full enterprise technology stack.

Responsibilities:

• Design and build production-grade agentic systems end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management and lifecycle observability
• Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets
• Integrate and abstract across multiple LLM providers , OpenAI, Anthropic, Vertex AI and open-source models , with fallback routing, token, cost and latency management
• Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling, cost and safety monitoring
• Embed directly with client engineering teams to design, prototype and deploy agentic solutions
• Build reusable patterns, accelerators and playbooks that scale beyond individual client engagements
• Define and use metrics to measure agent accuracy, latency, safety and cost-effectiveness; present findings and recommendations to client stakeholders in business terms

Basic Qualifications:

• 5+ years of software engineering experience in production environments
• Minimum 1 year of hands-on experience designing and deploying agentic AI solutions in a production environment
• Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen or equivalent
• Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code
• RAG pipeline ownership: embeddings, chunking strategy, vector databases and context engineering
• LLMOps fundamentals: eval harness design, prompt versioning and production observability
• Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD and IaC (Terraform or Helm)
• Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience