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DNV

AI Engineer - Agentic Systems

London
Posted about 23 hours ago
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About Us

We are the independent expert in assurance and risk management. Driven by our purpose, to safeguard life, property, and the environment, we empower our customers and their stakeholders with facts and reliable insights so that critical decisions can be made with confidence.

As a trusted voice for many of the world’s most successful organizations, we use our knowledge to advance safety and performance, set industry benchmarks, and inspire and invent solutions to tackle global transformations.

About Energy Systems

We help customers navigate the complex transition to a decarbonized and more sustainable energy future. We do this by assuring that energy systems work safely and effectively, using solutions that are increasingly digital. We also help industries and governments to navigate the many complex, interrelated transitions taking place globally and regionally, in the energy industry.

About The Role

At Digital and Data Solutions (DDS), we develop innovative software and data-driven solutions that help customers solve complex challenges in energy, infrastructure, and sustainability. Together, we combine technology and trusted expertise to create lasting impact and accelerate the transition to a more sustainable world.

We are looking for an AI Engineer specializing in agentic systems to help design, build, productise, and evolve generative AI capabilities within Horizon, cloud platform for renewable energy asset monitoring, analytics, optimisation, and decision support.

This is a hands-on, product-focused engineering role. You will build production-grade AI agents that interact with Horizon data, analytics, algorithms, APIs, documentation, and operational workflows. The focus will be on building a role-based multi-agent system supporting users such as Asset Managers, Asset Owners, O&M Managers, Traders, and Analysts.

What You’ll Do

  • Design and implement a scalable architecture for role-based AI agents, including agents supporting Asset Management, Asset Ownership, O&M, predictive maintenance, trading, and analytical workflows.
  • Define agents responsibilities, tools, interaction patterns, task delegation, context sharing, and hand-offs between specialised agents.
  • Integrate agents with diverse Horizon data sources, including operational time-series data, alarms, events, asset metadata, analytical results, forecasts, reports, logbooks, and technical documentation.
  • Build evaluation frameworks and representative test datasets covering answer quality, groundedness, tool selection, workflow completion, hallucination risk, safety, regression, latency, and operational reliability.
  • Implement observability and traceability across agent execution, including prompts, retrieved context, tool calls, model responses, decisions, failures, and user feedback.
  • Deploy and operate AI services in production, working with software and platform engineers.
  • Collaborate with renewable energy domain experts to ensure that agent outputs are technically meaningful, evidence-based, and appropriate for operational decision-making.
  • Stay informed about developments in LLMs, agent orchestration, multimodal systems, evaluation, and AI engineering, and assess them pragmatically for production use.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

What makes this role exciting: you’ll take cutting-edge agent-based systems out of the lab and into production, building AI that directly supports the operation and optimization of renewable energy assets at global scale.

What we offer

Our benefits package is specifically designed to support your physical, financial and social well-being:

  • Great atmosphere of working together with professionals and some of the most engaged and knowledgeable people in the industry,
  • Receive guidance from colleagues through coaching, mentoring and participating in international networks,
  • Advance your professional skills and technical expertise, through individual competence development plans and tailored training,
  • Be part of a world growing and renowned organization with origins dating back to 1864.

Other Than You Can Expect

  • Medical Scheme,
  • Commuting Allowance,
  • Life Insurance,
  • Pension Plan,
  • Kindergarten Allowance,
  • 40 hours per week with a flexible schedule. Friday
  • Home working allowance (up to 2 days per week),
  • 23 days of annual leave,
  • Employee Referral scheme.

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DNV is an Equal Opportunity Employer and gives consideration for employment to qualified applicants without regard to gender, religion, race, national or ethnic origin, cultural background, social group, disability, sexual orientation, gender identity, marital status, age or political opinion. Diversity is fundamental to our culture and we invite you to be part of this diversity.

Requirements

About you

  • Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, or a related field, or equivalent practical experience.
  • Proven experience building AI agents, agentic workflows, or AI assistants, preferably in production environments.
  • Experience with Retrieval-Augmented Generation (RAG), embeddings, vector search, and prompt engineering.
  • Strong Python software engineering skills and experience developing production-grade applications.
  • Experience integrating AI solutions with APIs, databases, and enterprise systems.
  • Familiarity with Git, CI/CD, Docker, and cloud-native development practices.
  • Strong communication skills and fluency in written and spoken English.

Nice To Have

  • Experience deploying AI workloads on Kubernetes.
  • Experience with self-hosted LLMs and model serving.
  • Familiarity with ClickHouse, MongoDB, vector databases and time-series data platforms.

You are curious, adaptable, and proactive, thriving in collaborative, fast-moving environments. You take ownership of projects, communicate complex AI concepts clearly to technical and non-technical stakeholders, and enjoy solving challenging real-world problems.

As part of the interview process, we ask you to submit a short report or demo of an AI agent you’ve built. This is your chance to showcase your hands-on skills and highlight your creativity.

Security and compliance with statutory requirements in the countries in which we operate is essential for DNV. Background checks will be conducted on all final candidates as part of the offer process, in accordance with applicable country-specific laws and practices.

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Skills

AI Agents
Agentic Workflows
RAG
Python
Prompt Engineering
Vector Search
Embeddings
API Integration
CI/CD
Docker
Kubernetes
Cloud-native Development
Git
Multi-agent Systems
LLM Orchestration
Observability

Location

London, England, United Kingdom

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