AI Operations Engineer – Internal Agents, Workflow Automation

Role Overview

• Discover & shape high-value AI opportunities (internal process focus)
• Partner with functional leaders to identify workflows where AI can remove friction, reduce cycle time, improve accuracy, or strengthen compliance.
• Map the current state process, identify bottlenecks and failure modes, and re-design the process to be automation-ready (clarify inputs/outputs, decision points, data sources, controls, and ownership).
• Define success metrics (time saved, error reduction, throughput, adoption, auditability) and translate business goals into a build plan.
• Build internal AI agents and automation tools (end-to-end ownership)
• Design and implement internal agents using modern LLM patterns (tool use/function calling, retrieval-augmented generation where needed, structured outputs, and human-in-the-loop checkpoints).
• Build whole-product solutions: lightweight UX, service/API layer, integrations, data access, and automation triggers—appropriate to the use case.
• Use AI-assisted development techniques to speed delivery while sustaining maintainability and readability.
• Operate, maintain, and scale (production mindset)
• Own reliability: monitoring, alerting, logging, incident response, and continuous improvements.
• Establish repeatable patterns for onboarding new workflows and scaling existing ones (templates, shared components, evaluation harnesses, documentation).
• Create and maintain runbooks and lightweight training so internal teams can adopt solutions confidently.
• Risk, control, oversight, security & compliance by design
• Implement appropriate guardrails: data minimization, access controls, secrets management, safe prompt/tooling patterns, output validation, and traceability.
• Ensure solutions meet internal security and compliance expectations (including audit readiness, change management discipline, and clear ownership).
• Maintain clear documentation of how systems work, what data they touch, and how risks are mitigated.
• Cross-functional coordination
• Coordinate across IT/Security, Legal/Privacy, and functional SMEs to get solutions approved and adopted.
• Communicate progress with crisp updates; manage tradeoffs between speed and rigor.
• Outcomes to be achieved
• A portfolio of high-impact internal AI agents deployed into real workflows (not demos), with measurable business outcomes.
• A scalable operating model for internal AI: reusable components, clear governance, and a predictable path from idea → production.
• Reduced process friction through AI + process redesign, not AI bolted onto broken workflows.
• High trust in outputs through appropriate controls, auditability, and operational reliability.
• Working style / What success looks like here
• You are low ego, high output: you can operate independently, but you collaborate naturally and bring others along.
• You can move fast without being reckless: you know where to be scrappy and where to add rigor.
• You care about outcomes: automation only matters if it changes how people work.

Requirements

• Demonstrated ability to build and maintain end-to-end software (design → build → deploy → operate), with strong engineering fundamentals.
• Proficiency in at least one modern programming language (e.g., Python, TypeScript, C#, Node.js) and comfort learning what’s needed.
• Practical experience integrating systems via APIs, authentication, and structured data formats.
• Strong ability to work with non-technical stakeholders: translate ambiguous problems into clear specs, iterate quickly, and drive adoption.
• Experience building cloud-based services and the surrounding engineering hygiene (CI/CD, source control, test automation, and operational monitoring).
• Comfort with secure and scalable platform concepts (networking, identity, secrets, infrastructure automation).
• Experience or strong interest in AI-assisted development as part of daily engineering practice.
• Hands-on experience building LLM-powered tools/agents (prompting, tool use, retrieval where appropriate, and evaluation/quality approaches).
• Ability to design safe and predictable AI systems (validation, fallbacks, human-in-the-loop, and clear failure handling).
• Familiarity with enterprise security/compliance expectations (access controls, audit trails, change management, data governance).
• Experience modernizing processes (Lean/ops mindset) and designing systems that align to how teams actually work.
• Experience building internal tools that drive adoption across multiple functions.

Tech Stack

• Cloud
• JavaScript
• Node.js
• Python
• TypeScript

Benefits

• As remote enabled company our employees enjoy the flexibility to establish their own life/work balance
• Matching 401K Plan (25% of employee's contribution up to the IRS max)
• Health insurance (PPO and HDHP/HSA plans offered)
• Dental insurance
• Vision insurance
• Life insurance (1x employee salary)
• Short-term disability (employer paid)
• Long-term disability (employer paid)
• Flexible Spending Plan (medical and dependent)