Senior AI Engineer (Agentic Systems)

TL;DR

Senior AI Engineer (Agentic Systems): Leading the design and delivery of agentic systems that orchestrate tools, data, and policies for enterprise workflows with an accent on multi-agent architectures, RAG, and MLOps. Focus on building modular components like planners and tool registries, implementing deterministic fallbacks, and creating robust evaluation harnesses.

Location: Remote (Must be US-based)

Company

A leader in delivering secure, customizable generative AI solutions and managed services for enterprises.

What you will do

• Design multi-agent architectures with state management, memory, and routing using frameworks like LangGraph, AutoGen, or CrewAI.
• Integrate enterprise data sources via function calling, webhooks, and RAG patterns with vector stores (Azure AI Search, pgvector, Pinecone).
• Implement reliability measures including SLIs/SLOs, tracing (Langfuse, OpenTelemetry), and deterministic fallbacks.
• Create evaluation harnesses using Ragas and DeepEval to measure groundedness, task success, and safety.
• Enforce safety and governance policies as code, ensuring compliance with ISO 27001, SOC 2, and GDPR.
• Collaborate with enterprise clients to translate business processes into production-ready agentic designs.

Requirements

• 5–8+ years in software/platform engineering with production LLM application experience.
• Expertise in agentic frameworks (e.g., LangChain, AutoGen, LlamaIndex) and tool-calling patterns.
• Strong RAG engineering skills, including vector DBs, chunking/embedding strategies, and grounding techniques.
• Experience building observable and secure LLM systems (tracing, evals, guardrails, IAM).
• Proficiency in Python, TypeScript, async patterns, APIs, and CI/CD.
• Must be based in the United States.

Nice to have

• Azure-first experience (Azure OpenAI, AI Studio, AKS, Key Vault).
• Experience with AWS/GCP and enterprise connectors like Salesforce or ServiceNow.
• Knowledge of structured output, constrained decoding, and JSON Schemas.

Culture & Benefits

• High ownership and velocity environment in a small, agile team.
• Strong focus on security-by-design and data governance as core priorities.
• Data-driven approach to improving task success and grounding.
• Learning and sharing culture with deep dives and support for certifications.
• Inclusive and flexible workplace with remote-first options.