Job DescriptionTechnical Manager - LLMs, RAG and ML is a strategic role within the Product organization, reporting to the Head of Section - AI Solutions. This role is responsible for translating applied AI strategy into customer-ready capabilities, prototypes, reusable technical patterns, evaluation methods, and production-oriented solution designs that support the Transformational Trust Initiative and broader digital platform enablement across Energy Systems.
This role is responsible for translating applied AI strategy into customer-ready capabilities, prototypes, reusable technical patterns, evaluation methods, and production-oriented solution designs that support the Transformational Trust Initiative and broader digital platform enablement across Energy Systems.
This role sits within Digital & Transformation and operates as a core product partner to the AI Solutions function, working across advisory regions, Renewable Certification, Digital & Data Solutions, Global Service Area Leads, engineering, data science, UX, and domain experts.
This position collaborates directly with the Head of Section - AI Solutions to identify high-impact AI opportunities, define product requirements, validate prototypes and proofs-of-concept, and support the delivery of scalable AI-driven workflows across Energy Systems.
This role is based at Oakland, CA, Irvine, CA office. What You'll DoAI Product Strategy & Roadmap Contribution- Partner with the Head of Section - AI Solutions to translate the applied AI strategy into an executable technical roadmap, delivery plan, and prioritized set of AI product capabilities
- Contribute to roadmap definition, product vision, and technical strategy for LLM-enabled workflows across the Transformational Trust platform.
- Identify high-impact opportunities where AI, language models, retrieval systems, and automation can improve customer value, workflow efficiency, decision quality, and platform adoption.
- Help define technical standards, delivery patterns, and reusable components for AI-powered product development across advisory and digital platform workflows.
- Provide informed recommendations on model selection, retrieval architecture, evaluation approach, prompt strategy, orchestration patterns, and technical feasibility.
LLM, RAG and AI Solution Development - Design, prototype, and guide delivery of AI-enabled capabilities using Large Language Models, generative AI foundations, Retrieval-Augmented Generation, vector search, and structured output techniques.
- Develop proof-of-concepts, reference implementations, and solution designs that engineering partners can implement, scale, and maintain.
- Design retrieval and indexing approaches for complex document, language, and workflow data, including semantic search, and context construction.
- Apply prompt engineering, tool/function calling, structured reasoning, and multi-step workflow patterns to support reliable AI-enabled product experiences.
- Support fine-tuning, LoRA, model adaptation, and evaluation approaches where needed to improve domain performance, task reliability, and user outcomes.
AI Evaluation, Quality and Responsible Use- Establish practical evaluation methods for LLM-enabled workflows, including accuracy, relevance, reliability, retrieval quality, user experience, and task completion metrics.
- Develop benchmark approaches, test datasets, evaluation rubrics, and monitoring methods to support reliable AI performance over time.
- Partner with the Head of Section, data science, engineering, and governance stakeholders to support responsible AI practices, including transparency, risk identification, data considerations, and appropriate human oversight.
- Define quality standards for prototypes, AI components, prompt patterns, retrieval workflows, and production handoffs.
- Track and communicate AI product performance against KPIs tied to customer value, workflow efficiency, model quality, and responsible AI outcomes.
Cross Functional Technical Leadership- Lead cross-functional AI delivery efforts across product, engineering, data science, UX, domain experts, and customer-facing teams.
- Serve as a technical translator between business needs, user workflows, AI methods, and engineering implementation.
- Provide technical guidance to teams working on LLM applications, retrieval systems, chatbot or agentic workflows, data pipelines, and AI-enabled decision support.
- Support rapid prototyping and iteration while maintaining a disciplined approach to quality, scalability, and responsible deployment.
- Coach emerging AI and product talent as the AI Solutions function grows, helping build a culture of experimentation, rigor, inclusion, and continuous improvement.
Responsibilities- Generous paid time off (vacation, sick days, company holidays, personal days)
- Multiple Medical and Dental benefit plans to choose from, Vision benefits
- Spending accounts - FSA, Dependent Care, Commuter Benefits, company-seeded HSA
- Employer-paid, therapist-led, virtual care services through Talkspace
- 401(k) with company match
- Company provided life insurance, short-term, and long-term disability benefits
- Education reimbursement program
- Flexible work schedule with hybrid opportunities
- Charitable Matched Giving and Volunteer Rewards through our Impact Program
- Volunteer time off (VTO) paid by the company
- Career advancement opportunities
**Benefits vary based on position, tenure, location, and employee election**For California, Washington, New York, Washington, D.C., Illinois, and Maryland: "DNV provides a reasonable range of compensation for this role. The actual compensation is influenced by a wide array of factors, including but not limited to skill set, level of experience, and specific location. For the states of California, Washington, New York, Washington, D.C., Illinois, and Maryland only, the starting pay range for this role is $120,000 - $160,000.
QualificationsWhat is Required- Bachelor's degree required
- 5+ years of relevant experience
- Significant hands-on experience designing, developing, evaluating, or delivering LLM-enabled capabilities in digital products, applied AI solutions, or customer-facing platforms
- Demonstrated experience with Retrieval-Augmented Generation, vector search, semantic retrieval, indexing strategies, or related methods for working with large text or document datasets
- Experience developing or applying LLM evaluation methods, model quality metrics, benchmark approaches, prompt evaluation, chatbot evaluation, or human-centered AI assessment methods
- Strong understanding of prompt engineering, structured outputs, tool/function calling, model orchestration, and practical techniques for improving reliability in LLM-enabled workflows
- Experience contributing to product strategy, technical roadmaps, product discovery, solution design, or prioritization of AI-enabled capabilities
- Demonstrated track record delivering AI, machine learning, NLP, chatbot, language modeling, or data science products from concept through implementation or production handoff
- Ability to work directly with engineering, data science, UX, product, business stakeholders, and customer-facing teams to translate complex needs into scalable technical solutions
- Strong communication skills, including the ability to explain AI concepts, tradeoffs, risks, and product implications to both technical and non-technical audiences
- Experience leading cross-functional initiatives, technical workstreams, or small teams in a product, AI, data science, or technology environment
- Strong written and verbal English communication skills
- We conduct pre-employment drug and background screening
What is Preferred- Master's degree or equivalent advanced experience in data science, machine learning, artificial intelligence, computer science, or a related field
- Experience with FAISS or similar vector indexing, embedding, semantic search, or retrieval technologies
- Experience with fine-tuning, LoRA, model adaptation, synthetic data generation, or custom objective functions for language models
- Experience developing AI-enabled workflows for advisory, evaluation, due-diligence, risk, compliance, technical review, customer support, or knowledge-intensive professional services
- Familiarity with responsible AI frameworks, data governance, privacy considerations, or model risk management
- Experience delivering customer-facing products or internal platforms using AWS or comparable cloud environments
- Background in complex, technical, regulated, or high-trust sectors
*Immigration-related employment benefits, for example visa sponsorship, are not available for this position*#LI-DNI
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