AI Engineer
Skills
About the role
Job Description
AI Engineer
Location: Indianapolis, IN
Remote
Engineering & Technology
About The Role
Kobie is building an internal agent platform on Amazon AgentCore that automates analyst workflows, surfaces insights from program data in Snowflake, and gives teams and clients an LLM-native way to work with complex loyalty logic. We are looking for a hands-on AI Engineer to ship on that platform: building agent harnesses, writing the tools those agents call, and owning the reliability and evaluation of what goes to production. This is not a research role; you will prototype, ship, monitor, and iterate on features used by real teams.
Responsibilities
Build agent harnesses in Python using LangChain and LangGraph, including tool-calling, structured outputs (Pydantic/JSON schema), retries, streaming, and memory
Package agent harnesses for the AgentCore Runtime with appropriate context, tools, skills, and subagents that fit cleanly into production flows
Write the tools and skills agents use: API integrations, SQL queries against Snowflake, Snowflake-backed knowledge retrieval with clear contracts and Pydantic validation
Build evaluation harnesses (golden datasets, LLM-as-judge, regression suites) using AgentCore Evaluations and wire them into CI
Implement guardrails around tool execution: auth scoping, input/output validation, PII and prompt-injection protections, and hallucination mitigation
Own what you ship: prototype, deploy through Amazon AgentCore, monitor traces, and fix it when it breaks
Partner with data engineers on Snowflake-backed retrieval patterns (Cortex Analyst and Cortex Search Services)
Contribute to refining internal engineering patterns as the stack evolves
Required Skills
3+ years of professional Python, with production experience building and operating services
1+ years of hands-on work with LLMs in production: prompt/context engineering, tool/function calling, structured outputs, RAG
Working knowledge of LangChain/LangGraph or a comparable framework (AgentCore Strands, CrewAI, or Semantic Kernel)
Experience with LLM observability tools: Amazon CloudWatch, LangSmith, Langfuse, MLflow, or OpenTelemetry
Experience designing evaluation frameworks (MLFlow, DeepEval, LLM-as-judge, multi-turn regression)
Fluency with Git, Docker, and modern API frameworks
Clear written communication and judgment to know when something is ready to ship
A bachelor's degree is not required; equivalent practical experience (bootcamps, self-taught work, career changes, non-CS technical degrees) counts
Strongly Preferred Skills
Hands-on experience with Amazon Bedrock and/or AgentCore as a developer: runtime, gateways, memory, policy, guardrails, observability, awscli, evaluations
Experience with Snowflake, Snowpark, or Snowflake Cortex
Fluency in writing and reading SQL, as well as understanding semantic models
Familiarity with multi-agent patterns: supervisor/router, subagent/handoff, reflection, human-in-the-loop
A considered view on where agents should and shouldn't act and comfort pushing back when "let's add an agent" isn't the right answer
Experience in Loyalty, MarTech, AdTech, or a comparable data-rich B2B domain
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