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Senior AI Architect - Generative AI

GE Vernova · Posted Nov 5

Power generation, wind turbine, grid solution, and electrification services

300 Garlington Road, Greenville, South Carolina, 29615-4614, United States of America; EPIP 122 (Phase II), Whitefield Road, Bengaluru, Karnātaka, 560066, India; Roc Boronat 78, Barcelona, Barcelona, 08005, Spain; 1 River Road, Schenectady, New York, 12345-6000, United States of AmericaFull-timeOnsiteSenior Level10+ years₹45.0L–₹75.0L yearly65 applicants
EnergyPower GenerationRenewable EnergyElectrificationWind EnergyPublic Company
Full time

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About the role

The role sits within GE Vernova's Wind Engineering organization and serves as the technical authority for generative AI architecture. It focuses on foundation-model, RAG, conversational, and agentic solutions for enterprise knowledge systems, engineering copilots, document intelligence, automated workflows, and multi-agent applications. The architect will define reusable patterns and standards for model selection, retrieval, evaluation, guardrails, observability, integration, and human oversight.

What you will do

  • 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 selection criteria for hosted, enterprise, open-weight, fine-tuned, and task-specific models based on quality, security, latency, cost, controllability, and supportability.
  • Ensure solutions align with approved GE Vernova platforms, identity, data, integration, and deployment standards.
  • Define when deterministic automation, a single assistant, or an agentic architecture is appropriate.
  • Establish patterns for 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.
  • Prevent uncontrolled autonomy by defining bounded actions, approval gates, transaction limits, and recoverable failure behavior.
  • Define evaluation frameworks covering task success, groundedness, retrieval quality, factuality, completeness, instruction adherence, safety, latency, cost, and user value.
  • Create representative test sets from actual engineering tasks, including difficult, ambiguous, adversarial, and out-of-scope cases.
  • Establish automated, model-based, deterministic, and expert human evaluation where each is appropriate, with 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 rather than creating disconnected chat interfaces.
  • 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 subject to appropriate validation.
  • 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.
  • Maintain a pragmatic view of emerging models and frameworks, adopting capabilities based on measured engineering value.

Skills used in this role

What the employer is looking for

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

Preferred qualifications

  • 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.

Benefits and support

  • medical, dental, vision, and prescription drug coverage
  • access to Health Coach from GE Vernova, a 24/7 nurse-based resource
  • access to the Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services
  • GE Vernova Retirement Savings Plan, a tax-advantaged 401(k) savings opportunity with company matching contributions 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
  • relocation assistance

About GE Vernova

GE Vernova logo

GE Vernova

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GE Vernova Inc. is a global energy company that provides equipment, services, and software to generate, transfer, orchestrate, convert, and store electricity. Operating through its Power, Wind, and Electrification segments, the company supports a broad customer base across more than 100 countries in powering economies and driving the energy transition. Formed as part of the strategic spin-off of General Electric's energy portfolio, GE Vernova is dedicated to electrifying and decarbonizing the world.

Industry
Energy
Company size
75000+ employees
Founded
2024
Location
Cambridge, Massachusetts, USA
Funding stage
Public Company

Leadership

SS
Scott Strazik

Chief Executive Officer and President

SF

Stephen F. Angel

Chairman of the Board

LL

Lola Lin

Chief Legal Officer and Secretary

RM

Roger Martella

Chief Corporate Officer, Chief Sustainability Officer & Head of Global Government Affairs

EG

Eric Gray

CEO, Power Segment

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