Defense Engines AI Transformation Leader
$176k - $235k/yr+ Annual discretionary bonus + Commission
Senior, Expert
Bachelor's, Associate's
Lynn, MA, USA+1 moreMore locations: Evendale, OH, USA
RemoteIn-person attendance is required for New Hire Orientation on Day 1. Travel of 10–50% is required.
ProductTechnical Product Management
No H1B Sponsorship
About the job
Requirements
- A bachelor's degree from an accredited university or college and at least 10 years of professional experience, or an associate's degree and at least 13 years of professional experience, or a high school diploma and at least 15 years of professional experience.
- At least 8 years of professional experience in information technology.
- Ability to travel 10–50%.
- Legal authorization to work in the United States is required; the employer will not sponsor employment visas.
- Hands-on forward-deployed engineering experience, personally producing working artifacts such as data pipelines, ontology and semantic models, notebooks, agent workflows, and functional user interfaces, with fluency in Python, SQL, or equivalent.
- Ability to move an idea across proof-of-concept, medium-fidelity, and high-fidelity stages under time pressure.
- Experience owning data platform and advanced analytics products at scale, including ingestion, modeling, governance, performance, and self-service consumption.
- Working fluency with modern analytics and artificial intelligence, including machine learning, large language models, retrieval, and agentic patterns, and judgment about where those methods are unsuitable.
- Working knowledge of manufacturing and maintenance, repair, and overhaul data and systems, including manufacturing execution systems, enterprise resource planning, quality, and shop-floor technology, and how their data informs delivery or inventory decisions.
- Deep technology, process, and domain expertise sufficient to influence product design for internally built or purchased products.
- Track record of understanding current and emerging technologies through training, job experience, or industry activities.
- Understanding of Lean Six Sigma principles and comfort operating within a Daily Management system.
Responsibilities
- Own the planning, forecasting, and production lifecycle for multiple interdependent data, analytics, and artificial intelligence products in the Defense Engines & Services delivery transformation program, and represent the customer in scope and sequencing tradeoffs.
- Build and maintain the data and analytics product roadmap, sequence it against constraints on engine and spare-part output, and identify and secure supporting stakeholders.
- Establish self-service data and analytics using manufacturing, quality, and delivery data so planners, buyers, and shop leaders can answer questions without opening a Digital Technology ticket.
- Operationalize and sustain value from advanced analytics and agentic artificial intelligence investments, and integrate proven prototypes into the operating model.
- Partner with central Digital Technology and Enterprise Data on data fabric and ontology adoption so manufacturing, quality, and delivery data is modeled once and reused across products.
- Take artificial-intelligence-enabled ideas from concept to working software; build low-fidelity proofs, advance successful concepts to medium- and high-fidelity prototypes using production data and real users, and determine which merit production investment.
- Embed with operators, planners, and engineers at the Genba, build capabilities with them, and stay involved until the capability is in use.
- Use rapid prototyping within Daily Management to turn Key Performance Indicator and Targets to Improve gaps into working capabilities within weeks.
- Define value cases in delivery terms, drive early benefits, report outcomes against 2026 measures, and stop or redirect work that does not improve delivery metrics.
- Influence Executive Band leaders and partner with business, finance, and Digital Technology leadership to align spending with value-stream priorities.
- Set data and artificial-intelligence standards across the Defense Engines & Services organization to maintain consistent use, implementation, support, and technical integrity.
- Mentor product managers and engineers in systems thinking and lean, experimental product practices, and improve the team's data and artificial-intelligence fluency.
- Manage supplier and contractor partners delivering analytics and artificial-intelligence work, hold them accountable for outcomes, and reduce dependence on external delivery.
- Lead portfolio risk management, including export control, cybersecurity, data governance, and responsible artificial intelligence, and design controls into products.
- Translate business problems into product bets, quantify value, and make tradeoffs across a multi-product portfolio based on business priorities.
- Establish performance metrics and drive continuous improvement across systems, processes, and resources.
- Evaluate decisions from the operator's perspective and partner with the business to shape future initiatives.
- Decompose problems and decide how to proceed when the problem or solution is not fully defined.
- Construct multiyear scenarios for data-centric methods and technologies under uncertainty, and interpret industry trends relevant to the roadmap.
- Set and change direction at the enterprise level by building direct and indirect support for ideas, largely without formal authority.
- Lead and influence across a complex matrix organization, including Executive Band leaders and their teams, while incorporating stakeholder input and making decisions.
- Direct and mentor others toward systems thinking for large-scale problems and remove roadblocks for the team.
- Own decisions, outcomes, and any necessary rework plans.
- Promote change, reward early adopters, and build a culture of proactive problem solving rather than reactive break-fix.
- Present concise facts and implications of alternatives to senior leaders and customers in writing and orally.
- Convert strategic vision into action plans with named owners and dates.
- Manage uncertainty for self and others and make decisions when problems or solutions are not fully defined.
- Remove barriers to others' creativity and promote simple, fast solutions.
- Prioritize work under pressure and tight deadlines using analytical, project-management, and organizational skills.
Desired Qualifications
- Green Belt certification is an example of demonstrated understanding of Lean Six Sigma principles.
About the company
GE Aerospace designs, builds and services jet engines and aircraft systems for airlines, plane makers and armed forces around the world. Through CFM International, a 50-50 venture with France's Safran, it makes the LEAP engine, the only engine on Boeing's 737 MAX and one of two offered on Airbus's A320neo family. Its other units make avionics and electrical power systems for civil and military aircraft. Most of its revenue comes from repairs, spare parts and long-term service deals that airlines buy over the decades each engine stays in use, with the work done in its own and partner shops. GE Aerospace traces to General Electric, founded in 1892, and is based in Evendale, Ohio.
Company Size
10,001+
Company Stage
Grant
Total Funding
$1B
Headquarters
Evendale, Ohio
Founded
1892
Get referred to GE Aerospace
See people who can refer or advise you
Simplify's Take
What believers are saying
- Demand outruns supply: orders rose 17% to $16.5 billion in the quarter to June 2026, lifting backlog above $210 billion.
- Hiring is broad: in March 2026, GE Aerospace set 5,000 US factory and engineering hires, after 5,000 in 2025.
- Factory investment is sustained: GE Aerospace has pledged over $2.5 billion to US plants and suppliers since 2024.
What critics are saying
- Its biggest deal adds debt: the $11.75 billion CPP castings purchase, agreed September 2026, mixes $7 billion cash with borrowing.
- Hourly pay follows a fixed track: Evendale and Erlanger's UAW contract sets 3% to 5% raises through 2029.
- Parts remain the choke point: castings shortages still slowed engine deliveries across the industry in September 2026.
What makes GE Aerospace unique
- Its engines fill the skies: about 50,000 commercial and 30,000 military GE and partner engines are in service.
- Lean methods shape daily work: staff follow FLIGHT DECK, GE Aerospace's own lean operating model built on continuous improvement.
- The Pentagon depends on it: GE engines power F-16 and F/A-18 fighters and Black Hawk and Apache helicopters.
Help us improve and share your feedback! Did you find this helpful?
Benefits
- Health Insurance
- Dental Insurance
- Vision Insurance
- Life Insurance
- Disability Insurance
- 401(k) Retirement Plan
- 401(k) Company Match
- Paid Vacation
- Parental Leave
- Adoption Assistance
- Relocation Assistance