Staff AI Process Engineer
$152k - $202kFull-time
GE Renewable Energy Power and Aviation
Job Description Summary You will identify, deconstruct, and re-implement high-value manual processes using AI agents, LLMs, and modern automation - replacing outdated bespoke tooling and undocumented expert intuition with transparent, verifiable, and scalable systems. You own the full arc: from ethnographic process discovery through to production agent orchestration with appropriate human oversight. The Problem You'll Solve
Every organization has processes that live in the heads of a handful of experts. These workflows are described as "more art than science," rely on tools that haven't been updated since they were written, and resist automation because nobody has properly decomposed what's happening. The experts are protective, the documentation is tribal, and the tooling is brittle. You will be the person who breaks these open. Job Description Job Responsibilities:
Every organization has processes that live in the heads of a handful of experts. These workflows are described as "more art than science," rely on tools that haven't been updated since they were written, and resist automation because nobody has properly decomposed what's happening. The experts are protective, the documentation is tribal, and the tooling is brittle. You will be the person who breaks these open. Job Description Job Responsibilities:
- Process Discovery & Knowledge Extraction
- Embed with domain experts to observe and document actual workflows (not the documented ones)
- Distinguish genuine expertise and edge-case reasoning from ritual, habit, and cargo-cutting
- Identify where "art" is pattern recognition that can be modeled, versus true judgment calls requiring human decision-making
- Produce formal process models from informal, oral-tradition knowledge
- Tool Replacement & Modernization:
- Audit legacy/bespoke tooling - identify what they do vs. what people think they do
- Design replacements using AI-native approaches (LLM pipelines, vision models, structured extraction) where appropriate, and conventional engineering where not
- Manage graceful deprecation of legacy tools without disrupting active operations
- Architect multi-step AI agent workflows that decompose complex expert tasks into verifiable stages
- Define tool-use patterns, context management, and failure/fallback strategies for agents
- Build evaluation frameworks that compare agent output against expert baselines
- Implement confidence-gated escalation - the system knows what it doesn't know
- Design the HITL topology: which decisions require human approval, review, or override
- Define escalation thresholds, audit trails, and feedback loops that improve the system over time
- Ensure experts transition from "doers" to "reviewers and teachers" without loss of engagement or institutional knowledge
- Build calibration mechanisms so human reviewers stay sharp (not rubber-stamping)
- Bachelor's degree from an accredited university or college
- Minimum of 5 years of experience in software/AI engineering with at least 2 years building LLM-based or agent-based systems
- Demonstrated ability to extract tacit knowledge from domain experts (process mining, cognitive task analysis, or equivalent)
- Experience designing and deploying AI agent orchestration (multi-step, tool-using, with evaluation)
- Strong systems thinking - can model a process end-to-end before writing a line of code
- Track record of replacing legacy systems without burning the house down
- Background in knowledge engineering, expert systems, or decision support
- Experience in Aerospace Industry or Aviation Regulatory organizations
- Familiarity with regulated or safety-critical environments where auditability matters
- Diplomatic persistence - experts will resist. You earn trust before you gain access
- Decomposition instinct - you see a 40-step manual process and immediately think in phases, decision points, and verifiable intermediate states
- Healthy skepticism - you don't automate what you don't understand; you don't trust the documentation
- Builder pragmatism - you ship the 80% solution with good HITL, not the 100% solution never
Vacancy posted a month ago
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