AI Agent Engineer

Job Description

AI Agent Engineer

Evanston, IL (On-Site)

Bear Claw is an AI-powered recruiting and applicant tracking platform built to help recruiters work smarter and place top talent faster. Our platform brings the recruiting workflow into one system—from candidate and job management to sourcing, outreach, and team collaboration.

At the center is Cora, our conversational AI assistant, which uses vector search and LLM-powered technology to identify candidate-job matches, surface opportunities, and help recruiters take action faster.

We are seeking an experienced AI Agent Engineer to help architect, build, and scale Cora , the AI intelligence layer within our recruiting and Applicant Tracking System (ATS).

This is a hands-on engineering role focused on building production-grade agentic AI systems that can understand recruiting workflows, retrieve and reason over structured and unstructured data, use tools, interact with external systems, and take controlled actions within our platform.

The ideal candidate has experience moving beyond basic LLM applications and RAG prototypes into production AI agents with orchestration, tool calling, memory, evaluation, observability, and appropriate human controls.

What You'll Build

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• Architect and develop agentic workflows that automate and assist complex recruiting processes.
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• Build agents that can reason across candidates, jobs, clients, recruiter activity, communications, and other ATS data.
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• Design tool-calling and MCP-based integrations that allow Cora to safely interact with internal services and external APIs.
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• Build and improve RAG and retrieval systems , including vector search, hybrid search, metadata filtering, reranking, and grounded responses.
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• Develop orchestration for multi-step and multi-agent workflows, including task routing, state management, context sharing, and escalation.
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• Design short- and long-term agent memory strategies where appropriate.
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• Implement guardrails, permissions, validation, and human-in-the-loop controls for agent actions.
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• Build evaluation frameworks for measuring retrieval quality, agent behavior, tool execution, accuracy, latency, and cost.
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• Integrate AI services with our existing AWS infrastructure and application stack.
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• Develop production APIs and services using Python and modern backend frameworks.
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• Monitor, debug, and continuously improve agent performance in production.
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• Work directly with product and engineering leadership to take AI capabilities from concept through production.
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Required Experience

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• Strong Python engineering experience and experience building production backend services/APIs.
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• Hands-on experience building LLM-powered agents or agentic applications in production.
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• Experience with frameworks such as LangGraph, LangChain, OpenAI Agents SDK, or comparable orchestration technologies .
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• Strong understanding of tool/function calling, agent state, context management, and structured outputs .
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• Experience building RAG systems , including embeddings, vector databases/search, retrieval strategies, and grounding.
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• Experience integrating LLMs with internal systems, databases, APIs, and third-party services.
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• Experience with AWS and serverless/cloud architecture, including technologies such as Lambda, API Gateway, SQS/SNS, and related services.
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• Strong understanding of production concerns including authentication, permissions, observability, error handling, retries, testing, and security.
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• Ability to independently architect and deliver complex AI functionality from prototype through production.
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• Strong communication skills and comfort working directly with technical and business leadership.
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Strongly Preferred

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• Experience with MCP (Model Context Protocol) and building or consuming MCP servers/tools.
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• Experience with LangGraph or other stateful agent orchestration systems.
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• Experience with PostgreSQL and vector/semantic search.
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• Experience with hybrid retrieval, reranking, knowledge graphs, or advanced retrieval architectures.
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• Experience implementing LLM/agent evaluations, tracing, prompt/version management, and observability.
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• Experience with multiple model providers such as OpenAI, Anthropic Claude, and/or Google Gemini.
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• Experience building AI systems that safely perform actions rather than simply generate responses.
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• Experience with recruiting technology, ATS/CRM platforms, or other workflow-heavy SaaS applications.
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What We're Looking For

We're not looking for someone whose AI experience is limited to prompt engineering or adding a chatbot to an application .

We're looking for an engineer who understands how to turn LLMs into reliable software systems: giving agents the right context, connecting them to tools and data, controlling what actions they can take, evaluating their behavior, and making the entire system observable and dependable in production.

This role will have significant influence over the architecture and evolution of Cora and Bear Claw's

broader AI platform .

Perks

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• Competitive base salary with healthcare, dental, vision, and 401(k)
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• Work closely with a small team where you'll have direct impact on the product
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• High-performance, collaborative environment focused on building great technology
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• Multiple career advancement paths, including opportunities to develop specialized technical expertise or move into leadership
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