Senior AI Architect - Generative AI

GE Vernova

19h•$113,200 - $188,800

About The Position

The Senior AI Architect, Generative AI is the technical authority responsible for defining how foundation-model, RAG, conversational, and agentic solutions are designed, evaluated, integrated, governed, and operated across Wind Engineering. The role creates architectures and reusable patterns for enterprise knowledge systems, engineering copilots, document intelligence, automated workflows, and multi-agent applications, ensuring grounding, traceability, security, human oversight, and measurable value. It establishes disciplined model selection, retrieval design, evaluation, guardrails, observability, and ownership practices so that GenAI solutions are dependable engineering systems rather than demonstrations. The architect defines reference architectures and approved patterns; designs bounded, tool-integrated agent workflows; establishes evaluation, acceptance, release, and monitoring standards; and integrates GenAI experiences into engineering processes and existing applications. The role also mentors Embedded AI Architects, AI engineers, data scientists, and product teams, leads architecture and evaluation activities, and advances reusable GenAI capabilities.

Requirements

Bachelor's degree in Computer Science, Engineering, Applied Mathematics, Data Science, or a related technical field.
Significant hands-on experience architecting and deploying production generative AI, RAG, conversational, or agentic systems.
Demonstrated knowledge of foundation models, embeddings, retrieval, reranking, prompt/context engineering, structured generation, tool use, and model evaluation.
Experience with orchestration and application frameworks such as LangGraph, Semantic Kernel, n8n, or equivalent, without dependence on any single framework.
Experience integrating AI applications with enterprise APIs, identity, data platforms, document repositories, workflow systems, and observability services.

Nice To Haves

Advanced degree.
Experience designing test sets and evaluation pipelines for quality, groundedness, safety, regressions, latency, and cost.
Understanding of GenAI security risks, including prompt injection, data leakage, insecure tool use, and untrusted content.
Ability to define enterprise standards, document decisions, mentor teams, and communicate architecture trade-offs to technical and non-technical stakeholders.
Experience with engineering, scientific, manufacturing, service, or regulated knowledge workflows.
Experience with Azure OpenAI, Amazon Bedrock, Google Vertex AI, or comparable enterprise model platforms and model gateways.
Experience with vector and hybrid search, knowledge graphs, document parsing, multimodal models, fine-tuning, adapters, or synthetic-data generation.
Experience implementing agent evaluation, runtime tracing, policy enforcement, and approval-based action execution.
Familiarity with Responsible AI frameworks, model risk management, cybersecurity threat modeling, and audit evidence for AI systems.
Experience evaluating commercial GenAI platforms and balancing delivery speed against control, portability, ownership, and total cost.

Responsibilities

Define reference architectures for foundation-model applications, RAG, tool-using assistants, agentic workflows, document intelligence, and multimodal engineering use cases.
Establish approved patterns for model gateways, prompt and context management, retrieval, memory, tool invocation, orchestration, evaluation, logging, and user experience.
Define model selection criteria based on quality, security, latency, cost, controllability, and supportability, and ensure solutions align with approved GE Vernova platforms and standards.
Define when deterministic automation, a single assistant, or an agentic architecture is appropriate.
Establish patterns for agent planning, tool use, state, memory, handoffs, retries, approvals, termination, and exception handling.
Integrate agents with engineering applications, APIs, workflow engines, data systems, simulation tools, and enterprise services using least-privilege access.
Set boundaries for agent actions, approval gates, transaction limits, and recoverable failure behavior.
Define evaluation frameworks for task success, groundedness, retrieval quality, factuality, completeness, instruction adherence, safety, latency, cost, and user value.
Create representative test sets from engineering tasks, including difficult, ambiguous, adversarial, and out-of-scope cases.
Establish appropriate automated, model-based, deterministic, and expert human evaluation, including calibrated use of LLM-as-judge methods.
Require release gates, regression testing, red-team evidence, and post-deployment monitoring before broad adoption.
Design GenAI experiences that fit engineering decision points, standard work, document flows, and existing applications.
Define patterns for human review, structured output, source evidence, approvals, write-back, and exception handling.
Ensure generated content entering engineering records is identifiable, reviewable, and appropriately validated.
Partner with process owners to measure cycle-time, quality, adoption, and rework impacts.
Mentor Embedded AI Architects, AI engineers, data scientists, and product teams in GenAI system design and evaluation.
Lead architecture reviews, evaluation clinics, red-team exercises, technical demonstrations, and reusable-pattern workshops.
Define competency expectations across RAG, agents, evaluation, security, prompt/context engineering, and workflow integration.
Evaluate emerging models and frameworks and adopt capabilities based on measured engineering value.

Benefits

Medical, dental, vision, and prescription drug coverage.
Access to Health Coach from GE Vernova, a 24/7 nurse-based resource.
Employee Assistance Program with 24/7 confidential assessment, counseling, and referral services.
GE Vernova Retirement Savings Plan, including a tax-advantaged 401(k) savings opportunity with company matching and company retirement contributions.
Access to Fidelity resources and financial planning consultants.
Tuition assistance.
Adoption assistance.
Paid parental leave.
Disability benefits.
Life insurance.
12 paid holidays.
Permissive time off.
Discretionary annual bonus eligibility.
Relocation assistance.