# Elios AI — Head of Artificial Intelligence

- Generated: 2026-08-20 09:37:02 PM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4455456507/
- LinkedIn job ID: 4455456507
- Client: Confidential industrial-technology company represented by Elios AI
- Posting age at fetch: 1 day ago (exact timestamp not publicly exposed)
- Applicants at fetch: Over 200 applicants
- Work model/location: Remote, United States
- Compensation: $250,000-$300,000 base, 15%-20% annual bonus, and equity
- Travel: Not disclosed
- Authorization: U.S. citizens and Green Card holders; no sponsorship
- Positioning track: Executive leader
- Fit outcome: PASS — 86%

## Fit decision

PASS. Keith directly matches the role's central build mandate: AI strategy, AI-organization design, production AI/ML, operating-model governance, executive communication, and hands-on technical leadership. Compensation and remote-work gates pass. Predictive-maintenance, rotating-equipment condition monitoring, signal processing, and physics-based anomaly detection are material but non-mandatory domain gaps and are not claimed.

## Weighted evidence map

| Requirement | Weight | Evidence score | Evidence |
|---|---:|---:|---|
| Own AI strategy, portfolio and product alignment | 3 | 3 | Defined AI strategy and product/platform roadmaps at IDW; built AI/ML practice at NorthBay; led transformation portfolios at TriMark and MassMutual. |
| Build and lead ML engineering, research and AI-engineering capability | 3 | 3 | Recruited and technically led 11 IDW engineers, seven SuccessKPI engineers, 24 NorthBay engineers, and global AWS communities totaling 180+ specialists. |
| Establish intake, prioritization, evaluation and governance operating mechanisms | 3 | 3 | Direct IDW Agile/product operating model, MassMutual AI governance, TriMark use-case prioritization, and AWS architecture standards. |
| Direct physics-based anomaly detection and reliability intelligence | 3 | 1 | Direct forecasting, optimization, predictive analytics and connected-device monitoring; no explicit rotating-equipment, signal-processing or physics-model ownership. |
| Maintain hands-on modern AI, production ML and MLOps credibility | 3 | 3 | Hands-on LLM, RAG, agents, LangChain/LangGraph, MCP, Python, AWS, SageMaker, TensorFlow, evaluation and production platform delivery. |
| Bring 10+ years leading AI/ML/data teams with hiring and org design | 3 | 3 | More than 25 years leading technical teams and repeated direct hiring, team building, mentoring and organizational design. |
| Connect technical decisions to customer value and revenue | 2 | 2 | Product commercialization, customer discovery, quantified workflow acceleration and savings; less direct ownership of a mature revenue function. |
| Communicate AI impact to CEO, executives and board-level audiences | 2 | 3 | Direct C-level advisory, strategy presentations, 50+ technical talks/workshops, and quantified executive transformation reporting. |
| Industrial technology, predictive maintenance or manufacturing | 1 | 1 | Connected industrial product/cloud delivery and manufacturing customer exposure; predictive maintenance is not direct. |
| AWS and modern cloud data platforms | 1 | 3 | Fifteen years of AWS experience, four years at AWS, and direct cloud/data-platform architecture and delivery. |

Weighted result: 62 of 72 possible points = 86.1%, rounded to 86%.

## Direct-match strengths

1. AI strategy tied to product roadmaps, portfolio prioritization and operating outcomes.
2. Repeated AI, data and engineering team construction, hiring and development.
3. Production GenAI, applied ML, cloud, MLOps, evaluation and governance credibility.
4. Hands-on/player-coach leadership combined with executive communication.
5. Quantified delivery: 70+ automations, 20+ workflows, eight-month product release, up to 50x acceleration, and 200+ AWS enterprises advised.
6. Forecasting, optimization, predictive analytics and connected-device/cloud experience.

## Material gaps and caveats

1. No explicit rotating-equipment predictive-maintenance or condition-monitoring background.
2. Signal processing, physics-based anomaly detection and reliability engineering are not directly documented.
3. Elios AI is recruiting for an unnamed industrial-technology client, limiting employer-specific diligence.
4. More than 200 applicants were shown at fetch.
5. Travel is not disclosed.

## Full normalized job description

Head of AI Location: Remote, United States Type: Full-time, permanent Compensation: $250,000 to $300,000 base, plus a 15 to 20% annual bonus and equity Authorization: U.S. citizens and Green Card holders only. No visa sponsorship available. About Us We are an industrial technology company changing how manufacturers care for the machines they depend on. Our condition monitoring platform pairs purpose-built sensor hardware with predictive analytics to catch equipment failures weeks before they happen, which keeps plants running and saves our customers millions in unplanned downtime. We are growing fast, backed well, and building for the long haul. About the Role This is a build role, not a maintain role. AI is already happening across our business, and it is happening in pockets: a model here, an experiment there, a promising prototype somebody spun up between sprints. Your job is to turn that scattered energy into a real operating capability with a strategy behind it, guardrails around it, and measurable business results coming out of it. You will report directly to the CEO and own AI end to end. That means setting the strategy through 2027, standing up the team to execute it, and deciding what we build, what we buy, and what we stop doing. You will also inherit our Data Science function, where the core technical challenge is genuinely interesting: physics-based models applied to high-frequency sensor data to detect anomalies in rotating equipment and translate them into reliability intelligence our customers act on. This role sits at the intersection of hands-on and executive. You will be in the architecture conversations and the model reviews, and you will also be the person presenting AI impact to the leadership team and the board. If you only want one of those two things, this is not the right fit. What You'll Do Define and own the company's AI strategy, tied to the product roadmap and revenue plan through 2027 Build and lead the AI organization across Machine Learning Engineering, ML research, and AI Engineering, including hiring, structure, and leveling Stand up the operating system for AI: intake, prioritization, evaluation criteria, and governance guardrails for tooling and data access Direct the evolution of our physics-based anomaly detection and reliability intelligence models Partner with Product, GTM, Customer Success, and Operations to find the AI applications that actually move customer outcomes, and to kill the ones that do not Define the metrics that prove AI impact, then report against them to the executive team What You'll Bring 10+ years leading AI, ML, or data science teams, including responsibility for hiring and org design A track record of shipping large-scale technical initiatives in companies that move quickly and change often Real hands-on fluency with modern AI, production ML systems, and MLOps. You can still read the code and challenge the approach Business judgment that connects technical decisions to customer value and revenue, not just model performance Bachelor's degree in Computer Science, Data Science, AI, Engineering, or a related field Nice to Have Advanced degree (MS, PhD, or a technology-focused MBA) Background in industrial technology, predictive maintenance, or manufacturing Deep experience with time-series data, signal processing, and anomaly detection AWS and modern cloud data platform experience Why Join Us You get a rare combination here: a clean slate on AI strategy, a CEO who wants you in the room, and a problem space where the models have obvious physical consequences. When your anomaly detection works, a plant does not shut down. That feedback loop is a lot more satisfying than a click-through rate.

## Artifact metadata

- Resume: https://bit.ly/4cRyf7U
- Cover letter: https://bit.ly/4g9mGeD
- Direct resume: https://files.keithsteward.com/Elios_AI/Keith_Steward_Head_Artificial_Intelligence_4455456507_Resume.pdf
- Direct cover letter: https://files.keithsteward.com/Elios_AI/Keith_Steward_Head_Artificial_Intelligence_4455456507_Cover_Letter.pdf
- Archived JD capture: https://files.keithsteward.com/Elios_AI/Keith_Steward_Head_Artificial_Intelligence_4455456507_JD_capture.md
- Validation: 2-page resume (972 words); 1-page cover letter (249 words); profile 82 words; 42 supported technologies; geometry, annotations, text extraction, page balance, and public links verified.
- Google Drive used: No