Agentic AI Software Engineer

Role Description

As an Agentic AI Software Engineer you will:

• Design, build, and ship agentic AI features end to end, from detection and decision logic through safe action execution, in a cross-functional agile environment.
• Ground agent behavior in deterministic rules engines and governed data so every agent explains its reasoning and never acts outside permitted boundaries.
• Build and operate the LLM layer, including prompt architecture, structured outputs, confidence scoring, timeouts, and rules-only fallback paths.
• Implement safe patterns for agent actions, including idempotent operations, undo windows, retries with backoff, and immutable audit logging.
• Develop statistical detection and baseline logic that turns workforce data into ranked, explainable findings with business impact attached.
• Manage inference cost, latency, and model selection from development through production.
• Partner with QA on evaluation suites, shadow-mode rollouts, and the trust metrics that gate every agent capability, and mentor junior engineers along the way.
• Operate independently, setting priorities and goals while continuing to learn and grow technically.

Qualifications

• 6+ years of professional software development experience, including shipping LLM-backed or agentic features to production.
• Deep production experience with C#/.NET, SQL Server, and API design in systems where correctness has financial consequences, such as payroll, billing, or banking.
• Experience integrating LLM APIs into enterprise applications, with structured outputs, retrieval grounding, and evaluation-driven iteration.
• Working fluency with statistical techniques on time-series data, such as rolling baselines, outlier detection, and threshold tuning.
• The ability to understand requirements and solve technical issues without supervision, serving as a technical lead.

Requirements

• Hands-on daily use of AI coding assistants or agentic tools, such as Claude Code, GitHub Copilot, or Cursor.
• Production experience with LLM APIs, MCP servers, or internal AI tooling.
• An understanding of human-in-the-loop agent design and write-capable AI.
• A clear understanding of LLM failure modes, including hallucination, prompt injection, and cost overrun, plus the limits and risks of AI-generated code.
• Preferred: experience with multi-agent orchestration, evaluation harness design, or statistical anomaly detection.

Benefits

• Competitive salary
• 20 Days of PTO (Paid Time Off) and 13 days of companywide holidays
• 8 hours to volunteer and impact the community
• Comprehensive benefits (Health/Dental/Vision/401K)
• Employee Choice Pre-Tax Benefit