Mid-Level AI Software Engineer

Insight Global
Southlake, TX, United States
12 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Compensation
$130,000.0 - $145,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Cursor Programming Tools Open Source Technology Software Engineering Software Factory Large Language Models Claude Code Agentic-AI Build Management Production Code Invoking Functions
+1 more
Model Context Protocol

Job description

Our client is building a software factory: an engineering system in which AI agents, working inside guardrails our engineers design, carry work from a well-formed specification through code, tests, review, and release. We are hiring Senior AI Engineers to build it. This is a hands-on, senior individual-contributor role for engineers who have already shipped real systems with LLMs and agents, and who want to apply that experience to how an entire engineering organization builds software.

You will design and build the agents, workflows, context systems, evaluation harnesses, and governance layer behind our AI-Led Development Cycle (AI-DLC), and you will prove them on production code across our platforms - not on sandbox demos. You will work closely with engineering leadership, the AI Engineering Group, Product, QA, and Security, and you will have real influence over the architecture and standards the rest of the organization adopts.

Requirements

  • 3-5 years of professional software engineering experience, including shipping and supporting production code

  • Hands-on experience building at least one real system with LLMs - an agent, a tool-calling workflow, retrieval, or AI-powered developer tooling - that went beyond a demo. Professional experience is preferred; substantial side projects or open-source work also count.

  • Daily fluency with agentic coding tools (for example Claude Code, Cursor, Codex, or similar), and an informed view of where they help and where they fall short.

  • Working knowledge of prompt and spec design, tool and function calling, and the Model Context Protocol (MCP) or similar integration patterns.

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