AI Engineer - Agentic Systems & Back-end Architecture

AI Engineer - Agentic Systems & Back-end Architecture

Summary

We are looking for a resourceful engineer who can take a loosely defined problem, figure out a smart way to solve it, and build it. The work centers on LLM-powered and agentic systems, but the core skill we need is strong problem-solving and back-end architecture. We care much more about how you think than which specific tools you have used. This is not an ML training or data science role; it is for a builder who treats LLMs as a powerful new component in well-designed software systems.

Responsibilities

• Take ambiguous business problems, design a sensible approach, and deliver working solutions with minimal hand-holding.
• Build agentic workflows where LLMs reason, call tools, and interact with internal systems and APIs.
• Design and build the back-end services, APIs, and integrations that agents utilize.
• Decide when an LLM is the right tool and when conventional code is simpler and more reliable.
• Prototype quickly to test ideas, then harden what works.

Requirements

• Strong Python skills and solid back-end engineering fundamentals: API design, integrations, auth, data handling, and building services that work.
• Hands-on experience building with LLMs, especially agentic patterns like tool/function calling, multi-step workflows, and retrieval. Personal projects count.
• Ability to think abstractly, architect systems from vague requirements, and explain your reasoning clearly.
• A track record of figuring things out independently, learning new tools fast, finding creative workarounds, and shipping quality code; a tinkerer's mindset.
• Awareness of what makes agent systems trustworthy in practice (e.g., evaluating output quality, limiting what an agent can access, and handling failures gracefully).

Preferred

• Experience with data pipelines and orchestration: building DAG-based workflows (Airflow, Dagster, Prefect, Temporal, etc.) or medallion/lakehouse architectures (bronze, silver, gold layers on platforms like Databricks, Snowflake, or BigQuery).
• Experience in API and MCP development: designing and building APIs or MCP servers that expose internal systems and data to applications or AI agents.
• Experience with agent frameworks and platforms: LangGraph, CrewAI, Semantic Kernel, Google ADK, AWS Bedrock AgentCore, Google Vertex AI, Azure AI Foundry, or Microsoft Copilot.

This is a 12-month Contract opportunity with our Kansas City, MO client. Low-cost employee benefits, paid time off, paid Holidays, and a 401(k) (with an immediately vested company match) are available with TriCom during the contract period. H-1B visa sponsorship is not available for this position. No third parties, please.

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