AI Engineer – Enterprise AI Platform

Jobtailor; Chicago (IL); On-site; USD 140,000 - 180,000; Full time

Job summary

Jobtailor in Chicago seeks a software engineer to architect a hierarchical, agent-serving system and govern LLM calls for cost and reliability. You will wire Snowflake, Postgres, and internal APIs to agents, designing multi-agent workflows with LangGraph/LangChain and implementing RAG.

Role requires transforming department needs into precise specs, maintaining CI-driven checks, and mentoring engineers on agent patterns and evaluation methods.}

Qualifications

• 2+ years of software engineering with backend in Python
• Hands-on experience with LLMs, prompt engineering, tool/function calling
• Experience with agent orchestration patterns (LangGraph, LangChain)
• SQL and data warehouse proficiency; Snowflake preferred
• Ability to write and debug CTEs, window functions, and joins
• Direct experience directing AI coding assistants to generate/modify production code
• Specification-writing skills and API design understanding
• Familiarity with RAG architectures, vector stores, and eval-driven development
• Git and CI/CD practices
• Experience with MCP and related protocols

Responsibilities

• Build and extend a hierarchical agent-serving architecture routing questions through specialized agents
• Govern LLM calls through a gateway for cost attribution, rate limiting, and reliability
• Securely connect Snowflake, Postgres, and internal APIs to agents
• Design and wire multi-agent workflows using LangGraph, LangChain, or similar tools
• Implement RAG for department knowledge bases using hierarchical chunking and hybrid search
• Use Claude Code and similar tools to write, refactor, and test production code
• Translate requirements into structured specs, prompts, and tool schemas
• Maintain golden question sets and CI-based regression checks
• Apply security and cost controls including spend caps and human approvals
• Implement audit logging for tool calls and sessions tied to user identity
• Roll out agents from pilots to wider release
• Maintain versioned retrieval documents and prompt playbooks
• Collaborate with Sales/Marketing to scope capabilities and communicate tradeoffs
• Document architecture decisions and team knowledge
• Mentor engineers on agent-building patterns and evaluation design

Skills

Python

LLM Integration

LangGraph/LangChain

SQL Snowflake

AI Coding Assistant

Tools

Claude Code

MLflow

Airflow

Docker

AWS

Azure

GCP

Job description

Job Responsibilities

• Build and extend a hierarchical agent-serving architecture that routes questions through specialized agents
• Govern LLM calls through a gateway for cost attribution, rate limiting, and circuit breaking
• Securely connect Snowflake, internal Postgres, and internal APIs to agents via MCP or custom tool patterns
• Design and wire multi-agent workflows using LangGraph, LangChain, or comparable agentic approaches
• Implement RAG for department knowledge bases using hierarchical chunking, hybrid search, and selective retrieval
• Use Claude Code and similar AI coding tools to write, refactor, and test production code
• Translate department requirements into structured specifications, system prompts, tool schemas, and knowledge files
• Build and maintain golden question sets that run in CI and detect regressions
• Apply security and cost controls, including spend caps, rate limits, read-only enforcement, and human-approval gates
• Implement audit logging for tool calls, sessions, and human approvals tied to user identity
• Roll out agents progressively from pilot teams to wider release
• Maintain versioned, human-reviewed retrieval documents and prompt playbooks
• Partner with Sales, Marketing, and other stakeholders to scope agent capabilities and communicate tradeoffs
• Document architecture decisions, open questions, and team knowledge
• Mentor engineers on agent-building patterns, evaluation design, and validation discipline

Requirements

• 2+ years of software engineering experience with strong backend fundamentals in Python
• Hands-on experience building with LLMs, including prompt engineering, tool/function calling, structured output parsing, and rigorous model-output evaluation
• Experience with at least one agent orchestration pattern or framework, such as LangGraph, LangChain, or a manual tool-use loop
• Solid SQL and data warehouse proficiency; Snowflake experience strongly preferred
• Ability to write and debug CTEs, window functions, and joins
• Direct experience directing AI coding assistants such as Claude Code, Cursor, or GitHub Copilot to generate and modify production code
• Demonstrated specification-writing skill
• Understanding of API design, integration patterns, and data modeling
• Familiarity with LLM evaluation concepts, including golden test sets, LLM-as-judge, precision/recall for RAG, and eval-driven development
• Experience with Git and standard CI/CD practices
• Experience with Model Context Protocol (MCP) preferred
• Familiarity with RAG architectures, chunking strategies, hybrid dense/sparse search, pgvector or comparable vector stores, and cross-encoder reranking preferred
• Experience with MLflow for LLM observability preferred
• Experience with LLM API gateways or proxy layers preferred
• Familiarity with Airflow or comparable batch schedulers preferred
• Understanding of AI governance concepts preferred
• Experience translating a business unit's ambiguous ask into a scoped, shipped technical solution preferred
• Experience with Azure, AWS, or GCP and Docker/Podman preferred

Core Competencies

Demonstrates expertise in building and extending agent-serving architectures, integrating LLMs, and implementing robust data governance and security measures. Proficient in translating complex requirements into structured technical solutions while mentoring teams on best practices in agent development.

Highest-signal resume keywords

• Python Software Engineering
• LLM Integration and Prompt Engineering
• LangGraph or LangChain Experience
• SQL and Snowflake Proficiency
• AI Coding Assistant Direction

ATS Optimization Keywords

Hard Skills

• Backend Development
• Prompt Engineering
• API Design
• Data Modeling
• Specification Writing
• CI/CD Practices
• RAG Implementation
• Model Context Protocol (MCP)
• SQL Querying
• Version Control with Git

Soft Skills

• Mentoring
• Collaboration
• Communication

Industry Keywords

• Agent-Orchestration
• Data Warehouse
• Hybrid Search
• Audit Logging
• AI Governance

Tools & Technologies

• Claude Code
• MLflow
• Airflow
• Docker
• AWS
• Azure
• GCP