Senior AI Architect - Generative AI

GE Vernova•Greenville, NC

23h

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 while ensuring grounding, traceability, security, human oversight, and measurable value. It distinguishes demonstrations from dependable engineering systems through disciplined model selection, retrieval design, evaluation, guardrails, observability, and ownership practices. The architect defines reference architectures and approved patterns for models, prompts and context, retrieval, memory, tools, orchestration, evaluation, logging, and user experience. The role establishes criteria for model selection and ensures solutions align with approved GE Vernova platforms and enterprise standards. It designs bounded, tool-integrated workflows; sets evaluation and acceptance standards; and integrates GenAI into engineering decision points and existing applications with appropriate human review and validation. The position also mentors architects, engineers, data scientists, and product teams; leads architecture reviews, evaluation clinics, red-team exercises, demonstrations, and workshops; and develops reusable practices and competency expectations. GE Vernova describes the work environment as offering professional development, challenging careers, and competitive compensation. The U.S.-based salary range is $113,200 to $188,800, subject to geographic differentials and other factors, with eligibility for a discretionary annual bonus. Relocation assistance is provided.

Requirements

Bachelor's degree in Computer Science, Engineering, Applied Mathematics, Data Science, or a related technical field; an advanced degree is strongly preferred.
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 a single framework.
Experience integrating AI applications with enterprise APIs, identity, data platforms, document repositories, workflow systems, and observability services.

Nice To Haves

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.
Advanced degree in a related technical field.

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; ensure alignment with approved platforms and standards.
Determine when deterministic automation, a single assistant, or an agentic architecture is appropriate, and establish patterns for planning, tool use, state, memory, handoffs, retries, approvals, termination, and exceptions.
Integrate agents with engineering applications, APIs, workflow engines, data systems, simulation tools, and enterprise services using least-privilege access and bounded actions.
Define evaluation frameworks and representative test sets; establish appropriate automated, model-based, deterministic, and expert human evaluation methods.
Require release gates, regression testing, red-team evidence, and post-deployment monitoring before broad adoption.
Design GenAI experiences integrated with 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 engineering-record content is identifiable, reviewable, and 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.
Assess 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.
Professional development.
Competitive compensation.