Job Description

We are seeking an AI Architect to define and lead the technical blueprint for AI across Steam Power Service Outage values stream. You will be responsible for the reference architecture, platform standards, and governance that enable reliable, secure, and scalable AI solutions. In this role you will be responsible for collaborating and leading the architectural leadership over hands-on model building: setting strategy, closing data gaps through robust data architecture, defining validation frameworks, and enabling teams to deliver high-value AI use cases. You will act as the technical product lead for the SPS AI platform and partner closely with business owners to drive endorsement across Steam.

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Lead the End-to-end AI life cycle in the outage values stream: Owns problem framing, data architecture, meta-Data, model development, validation, deployment, monitoring, and continuous improvement. Combines product analytics along with GFSK (Global Fleet Service Knowledge) architectural ownership (roadmap, backlog, budget, value realization). Develop high-value outcomes that shapes fleet reliability, outage avoidance, maintenance efficiency, safety, and data compliance. Develop evolving AI governance, data privacy, cybersecurity, and model risk standards--decisions with enterprise-level consequences. Lead the SPS data knowledge and bridge this to Industrial standard. Own and maintain GSFK AI functionality and align and prioritize with values stream requirements. Design sustainable prompting, retrieval pipelines, guardrails, and evaluation framework and benefits. Drive rigorous evaluation design: Back testing, testing, user interface reviews, acceptance thresholds, and interpretability standards. Model risk management: Establishes controls, documentation (model cards), and safety-critical and reliability-sensitive use cases. Closing data gaps: Orchestrating lineage, quality rules, imputation/enrichment, and upstream remediation across multiple owners is a cross-functional leadership task. Own long-lived architecture choices: Schema, feature store, and pipeline designs lock in costs and agility. Aligns Product, Engineering, Security, Compliance, and domain SMEs; navigates trade-offs and escalations. Supports driving adoption, training, and process integration across diverse users. Reduces iteration cycles. Prioritization discipline: Balances quick wins vs. foundational build-out to avoid technical debt and rework.

Require Qualifications

Systems thinking and reusable architecture design. Business acumen to translate SPS value stream targets and goals into technical decisions and measurable outcomes. Clear communication and influence across technical and non-technical stakeholders. Leadership and mentorship; setting standards and elevating team practices.

Preferred Qualifications

Experience in power generation or industrial/energy domains. Expertise with LLM/RAG architectures, prompt governance, and evaluation. Knowledge of responsible AI and data governance frameworks; model risk management. Background in platform/technical product ownership and cost/performance trade-offs Familiarity with tools common in this space.

The ideal candidate would demonstrate success through the following metrics.

Reduced time to onboard new AI use cases via reusable components and standards. Deliver platform reliability (uptime), performance (latency/throughput), and cost efficiency. Bring to close critical data gaps and improved data quality/maturity. Compliance/audit readiness and fewer model risk incidents. Demonstrate business impact and bring an adoption across SPS use cases and regions.

Additional Information

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Relocation Assistance Provided:

No