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Position: Agentic AI Engineer

Location: Chicago, IL

Duration: 12+ Months

Key Responsibilities

Architecture & Design: Lead the design and implementation of stateful, multi-agent systems using frameworks like LangGraph, CrewAI, or AutoGen.

Agent Orchestration: Develop robust reasoning loops (e.g., ReAct, Chain-of-Thought) and manage complex state, memory, and task hand-offs between specialized agents.

System Integration: Build secure interfaces (e.g., using Model Context Protocol (MCP)) to connect agents with enterprise APIs, databases, and external tools.

Production Excellence: Own the deployment, monitoring, and observability of agents in production using tools like Langfuse or LangSmith to trace reasoning and optimize performance.

Guardrails & Safety: Implement human-in-the-loop (HITL) mechanisms, input/output validation, and ethical guardrails to ensure agents operate safely and within regulatory boundaries.

Leadership: Mentor junior engineers, define coding standards for non-deterministic AI outputs, and drive the technical roadmap for agentic systems.

Required Technical Skills

Programming: Deep proficiency in Python and experience with backend frameworks like FastAPI.

AI Frameworks: Hands-on expertise in LangChain, LlamaIndex, and agent-specific orchestration patterns.

Data Systems: Strong knowledge of Vector Databases (e.g., Pinecone, Chroma), RAG architectures, and knowledge graphs.

Cloud & DevOps: Experience deploying AI workloads on AWS, Azure, or Google Cloud Platform using Docker and Kubernetes.

Evaluation: Proficiency in building automated evaluation harnesses (e.g., LLM-as-a-Judge) to measure accuracy and reduce hallucinations.

Qualifications

Experience: 5 8+ years in software engineering, with at least 2+ years focused on GenAI/Agentic AI implementations.

Education: Bachelor s

About Tessera Labs Tessera Labs is redefining how enterprises adopt and operationalize Artificial Intelligence. Backed by Foundation Capital and led by a world-class founding team, we build multi-agent AI systems that can automate complex business workflows across platforms like SAP, Salesforce, Workday, Snowflake, MuleSoft, and more. Our mission: Bring real AI automation to the enterprise — with speed, precision, and measurable impact. We move fast, operate with extreme ownership, and build at the frontier of applied AI.

Job Summary

As we build to the next level, we’re looking for a top-quality AI engineer with a strong focus on AI agents - someone who knows how to leverage LLMs, both open-source and closed, in combination with complex tool-calling hierarchies and operational patterns.

This is an opportunity to build scalable, secure, and high-impact AI technologies for the future of enterprise. If you thrive in high-growth, fast-moving environments and are passionate about AI, ML, and AI agents, we want to hear from you.

Key Responsibilities

1. AI Agent Building (60%)
• Develop complex multi-step agentic pipelines around open- and closed-source LLMs.
• Build tools enabling AIs to interact with critical enterprise software platforms.
• Ensure AI designs align with business objectives and industry best practices.​

2. ML development and fine-tuning (30%)
• Create data generation and processing pipelines to train and fine-tune custom ML models.
• Implement and manage training and evaluation pipelines for LLMs.

3. Deployment and AI Systems Infrastructure (10%)
• Manage AI infrastructure across platforms such as AWS, Azure, or GCP.​
• Deploy inference endpoints and serve AI and LLM technologies as part of our core product infrastructure.

Required Qualifications
• Earned a Bachelor’s degree, Master's degree or Ph.D. in Computer Science, Engineering, or a related field.​
• 5+ years of experience in software engineering, platform engineering, or related roles.​
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