senior ai engineer

Octopus Energy

<div>
 <strong>
  About the role
 </strong>
 <br/>
 <p>
  Octopus was founded with a mission to use technology to accelerate us towards a low-carbon future. That&rsquo;s why we created Kraken - our own technology platform from scratch which now serves over 70 Million households and is a core reason why Octopus is the number one energy supplier in the UK. We do it by hiring clever, curious, and self-driven people, enabling them with modern tools and infrastructure and giving them lots of autonomy.
 </p>
 <br/>
 <p>
  <br/>
  We have been using GenAI in live, customer-facing environments since 2022, including one system that creates tens of thousands of high-quality emails for our Energy Specialists, combining our deep knowledge of the energy industry and the Octo communication style with customer-specific data from Kraken.
 </p>
 <br/>
 <p>
  <br/>
  We are now looking for a Senior AI Engineer. You will build and scale the systems that allow Octopus teams to use Generative AI models (LLMs, RAG, agents). You will be hands-on, working with a cross-functional team to build out flagship AI projects, and the platforms that enable others to succeed with Generative AI.
 </p>
 <br/>
 <p>
  <br/>
  You&rsquo;ll work on developing solutions that genuinely move us closer to Net Zero in a company passionate about building great technology to change the way customers use energy. You&rsquo;ll have wide open problems to solve, so you&rsquo;ll need to be comfortable with ambiguity, figuring out an approach and validating it fast.
 </p>
 <p>
  <p>
   <br/>
  </p>
  <strong>
   What you&rsquo;ll do
  </strong>
  <br/>
  <ul>
   <br/>
   <li>
    <br/>
    <p>
     <strong>
      Design and Develop AI Platform Services:
     </strong>
     Build reusable, scalable services that expose GenAI models, knowledge retrieval pipelines, and agent workflows to application teams.
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <strong>
      Knowledge Base Development:
     </strong>
     Build and maintain knowledge retrieval systems. Process heterogeneous documents like pdfs and build embedding pipelines that extract, chunk and embed into embedding models.
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <strong>
      AI Readiness:
     </strong>
     Process content from unstructured documents and make it AI ready: Optimize their structure, clear up text ambiguity, and embed rich machine-readable metadata.
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <strong>
      AI Ops, evals and observability:
     </strong>
     Set up framework for monitoring and evaluating AI output quality (relevance, accuracy, safety, drift, cost) and platform observability (latency, cost, usage).
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <strong>
      Centre of Excellence:
     </strong>
     Act as a centre of excellence for the whole business in the technical side of AI and LLMs usage, setting best practices and accelerating adoption.
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <strong>
      Governance and Guardrails:
     </strong>
     Create governance layers for implementing PII redaction, prompt filtering etc.
    </p>
    <br/>
   </li>
   <br/>
   <br/>
  </ul>
  <br/>
  <p>
   <br/>
  </p>
  <strong>
   What you&rsquo;ll need
  </strong>
  <br/>
  <ul>
   <br/>
   <li>
    <br/>
    <p>
     <strong>
      Deep GenAI &amp; RAG Expertise:
     </strong>
     2+ years of hands-on experience building and productionizing LLM applications, with deep technical knowledge of vector databases (e.g., Qdrant, Weavite, Pinecone, pgvector) and orchestration layers (e.g., LangGraph, LlamaIndex). Comfortable working with heterogeneous documents like pdfs. Experience working with re-ranking models.
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <strong>
      Production-Grade Asynchronous Python:
     </strong>
     Strong software engineering fundamentals with deep experience in asynchronous programming (asyncio, FastAPI) to handle highly concurrent, I/O-bound LLM and database calls.&nbsp;
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <strong>
      Advanced Context Engineering:
     </strong>
     Proven experience solving production RAG challenges such as context window management, metadata filtering and semantic routing. Experience leveraging coding harnesses like Claude code.
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <strong>
      Modern Software Practices:
     </strong>
     Mastery of Git, automated testing and CI/CD pipelines. Experience working with cloud platforms like AWS.
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <strong>
      Comfort with Ambiguity:
     </strong>
     Ability to rapidly prototype an approach, validate it with metrics, and pivot fast in a fast-moving environment.
    </p>
    <br/>
   </li>
   <br/>
   <br/>
  </ul>
  <br/>
  <br/>
  <strong>
   It would be great if you had
  </strong>
  <br/>
  <br/>
  <ul>
   <br/>
   <li>
    <br/>
    <p>
     <strong>
      GraphRAG Experience:
     </strong>
     Familiarity with Knowledge Graphs (e.g., Neo4j) and ontologies to enhance standard vector RAG with highly structured, interconnected corporate data.
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <strong>
      Local/Open-Weight Model Deployment:
     </strong>
     Experience deploying and fine-tuning open-weight models (like Llama 3 or Mistral) via frameworks like vLLM or Ollama to optimize token costs and privacy.
    </p>
    <br/>
   </li>
   <br/>
   <li>
    <br/>
    <p>
     <strong>
      Prompt Caching &amp; Cost Optimisation:
     </strong>
     Practical experience implementing semantic caching layers to drastically reduce LLM API billing and response latency.
    </p>
    <br/>
   </li>
   <br/>
   <br/>
  </ul>
  <br/>
  <br/>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <br/>
 <p>
  💚 Why else you'll love it here 💚
 </p>
 <p>
  <br/>
 </p>
 <p>
  &bull;
  <strong>
   💰 Wondering what the salary for this role is?&nbsp;
  </strong>
  Just ask us! On a call with one of our recruiters it's something we always cover as we genuinely want to match your experience with the correct salary. The reason why we don't advertise is because we honestly have a degree of flexibility and would never want salary to be a reason why someone doesn't apply to Octopus - what's more important to us is finding the right octofit!
 </p>
 <p>
  &bull; 🎉&nbsp;Octopus Energy Group is a&nbsp;
  <strong>
   unique culture
  </strong>
  . An organisation where people learn, decide, and build quicker. Where people work with autonomy, alongside a wide range of amazing co-owners, on projects that break new ground. We want your hard work to be rewarded with perks you actually care about! We were recently named the UK's top company to work for, and we ranked in the top ten in the Sunday Times Best Places to Work 2024. Our Group CEO, Greg has recorded&nbsp;a podcast about our culture&nbsp;and how we empower our people. We&rsquo;ve also been placed in the&nbsp;top 10 companies for senior leadership
 </p>
 <p>
  &bull; 🎁&nbsp;Visit our UK perks hub -&nbsp;Octopus Employee Benefits
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   <span>
    If this sounds like you then we'd love to hear from you. 🚀
   </span>
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  P.S. Our process usually takes up to 4 weeks, but we&rsquo;ll always do our best to flex around what works for you. Along the way, you&rsquo;ll chat with our recruitment team and your Recruiter will help you throughout different stages. Got any burning questions before then? Drop us a message at talent@octoenergy.com and we&rsquo;d love to help!
 </p>
 <p>
  <br/>
 </p>
 <p>
  <em>
   Are you ready for a career with us? We want to ensure you have all the tools and environment you need to unleash your potential.&nbsp;Need any specific accommodations?&nbsp;Whether you require specific accommodations or have a unique preference, let us know, and we'll do what we can to customise your interview process for comfort and maximum magic!
  </em>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <em>
   Studies have shown that some groups of people, like women, are less likely to apply to a role unless they meet 100% of the job requirements. Whoever you are, if you like one of our jobs, we encourage you to apply as you might just be the candidate we hire. Across Octopus, we're looking for genuinely decent people who are honest and empathetic. Our people are our strongest asset and the unique skills and perspectives people bring to the team are the driving force of our success. As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. Our commitment is to provide equal opportunities, an inclusive work environment, and fairness for everyone.
  </em>
 </p>
 <br/>
 <p>
  Where necessary, we sometimes use AI tools to help with parts of our hiring process, like reviewing applications or assessing responses.
  <br/>
  <br/>
  We&rsquo;re lucky to receive a huge amount of interest, so these tools help our recruiters manage that volume, not replace them. Ultimately, every hiring decision (for example, whether to progress your application or not) is always made by a real person in our Talent team.
  <br/>
  <br/>
  If you&rsquo;d like to know more about how we use your data, you can reach out to us via email at talent@octoenergy.com.  We&rsquo;re happy to help!
 </p>
</div>


Senior AI Engineer

<div><h3 class="jobSectionHeader"><b>About the role</b></h3>
<p>
Octopus was founded with a mission to use technology to accelerate us towards a low-carbon future. That&rsquo;s why we created Kraken - our own technology platform from scratch which now serves over 70 Million households and is a core reason why Octopus is the number one energy supplier in the UK. We do it by hiring clever, curious, and self-driven people, enabling them with modern tools and infrastructure and giving them lots of autonomy.</p><p><br>
We have been using GenAI in live, customer-facing environments since 2022, including one system that creates tens of thousands of high-quality emails for our Energy Specialists, combining our deep knowledge of the energy industry and the Octo communication style with customer-specific data from Kraken.</p><p><br>
We are now looking for a Senior AI Engineer. You will build and scale the systems that allow Octopus teams to use Generative AI models (LLMs, RAG, agents). You will be hands-on, working with a cross-functional team to build out flagship AI projects, and the platforms that enable others to succeed with Generative AI.</p><p><br>
You&rsquo;ll work on developing solutions that genuinely move us closer to Net Zero in a company passionate about building great technology to change the way customers use energy. You&rsquo;ll have wide open problems to solve, so you&rsquo;ll need to be comfortable with ambiguity, figuring out an approach and validating it fast.</p>
<h3 class="jobSectionHeader"><b>
What you&rsquo;ll do</b></h3><div>
<ul>
<li><p><b>Design and Develop AI Platform Services:</b> Build reusable, scalable services that expose GenAI models, knowledge retrieval pipelines, and agent workflows to application teams.</p>
</li>
<li><p><b>Knowledge Base Development: </b>Build and maintain knowledge retrieval systems. Process heterogeneous documents like pdfs and build embedding pipelines that extract, chunk and embed into embedding models.</p>
</li>
<li><p><b>AI Readiness:</b> Process content from unstructured documents and make it AI ready: Optimize their structure, clear up text ambiguity, and embed rich machine-readable metadata.</p>
</li>
<li><p><b>AI Ops, evals and observability: </b>Set up framework for monitoring and evaluating AI output quality (relevance, accuracy, safety, drift, cost) and platform observability (latency, cost, usage).</p>
</li>
<li><p><b>Centre of Excellence: </b>Act as a centre of excellence for the whole business in the technical side of AI and LLMs usage, setting best practices and accelerating adoption.</p>
</li>
<li><p><b>Governance and Guardrails: </b>Create governance layers for implementing PII redaction, prompt filtering etc.</p>
</li>
</ul></div><h3 class="jobSectionHeader"><b>What you&rsquo;ll need</b></h3><div>
<ul>
<li><p><b>Deep GenAI &amp; RAG Expertise: </b>2+ years of hands-on experience building and productionizing LLM applications, with deep technical knowledge of vector databases (e.g., Qdrant, Weavite, Pinecone, pgvector) and orchestration layers (e.g., LangGraph, LlamaIndex). Comfortable working with heterogeneous documents like pdfs. Experience working with re-ranking models.</p>
</li>
<li><p><b>Production-Grade Asynchronous Python: </b>Strong software engineering fundamentals with deep experience in asynchronous programming (asyncio, FastAPI) to handle highly concurrent, I/O-bound LLM and database calls.</p>
</li>
<li><p><b>Advanced Context Engineering: </b>Proven experience solving production RAG challenges such as context window management, metadata filtering and semantic routing. Experience leveraging coding harnesses like Claude code.</p>
</li>
<li><p><b>Modern Software Practices: </b>Mastery of Git, automated testing and CI/CD pipelines. Experience working with cloud platforms like AWS.</p>
</li>
<li><p><b>Comfort with Ambiguity: </b>Ability to rapidly prototype an approach, validate it with metrics, and pivot fast in a fast-moving environment.</p>
</li>
</ul><div><h3 class="jobSectionHeader"><b>It would be great if you had</b></h3>
<div>
<ul><li><p><b>GraphRAG Experience: </b>Familiarity with Knowledge Graphs (e.g., Neo4j) and ontologies to enhance standard vector RAG with highly structured, interconnected corporate data.</p>
</li>
<li><p><b>Local/Open-Weight Model Deployment:</b> Experience deploying and fine-tuning open-weight models (like Llama 3 or Mistral) via frameworks like vLLM or Ollama to optimize token costs and privacy.</p>
</li>
<li><p><b>Prompt Caching &amp; Cost Optimisation:</b> Practical experience implementing semantic caching layers to drastically reduce LLM API billing and response latency.</p>
</li>
</ul></div></div></div><div>\uD83D\uDC9A Why else you'll love it here \uD83D\uDC9A<br>
</div><div></div><br>
<ul><li><b>\uD83D\uDCB0 Wondering what the salary for this role is? </b>Just ask us! On a call with one of our recruiters it's something we always cover as we genuinely want to match your experience with the correct salary. The reason why we don't advertise is because we honestly have a degree of flexibility and would never want salary to be a reason why someone doesn't apply to Octopus - what's more important to us is finding the right octofit!</li><li>\uD83C\uDF89 Octopus Energy Group is a <b>unique culture</b>. An organisation where people learn, decide, and build quicker. Where people work with autonomy, alongside a wide range of amazing co-owners, on projects that break new ground. We want your hard work to be rewarded with perks you actually care about! We were recently named the UK's top company to work for, and we ranked in the top ten in the Sunday Times Best Places to Work 2024. Our Group CEO, Greg has recorded a podcast about our culture and how we empower our people. We&rsquo;ve also been placed in the top 10 companies for senior leadership</li><li>\uD83C\uDF81 Visit our UK perks hub - Octopus Employee Benefits</li></ul><div></div><div><b><br>
If this sounds like you then we'd love to hear from you. \uD83D\uDE80</b></div><div></div><div><br>
P.S. Our process usually takes up to 4 weeks, but we&rsquo;ll always do our best to flex around what works for you. Along the way, you&rsquo;ll chat with our recruitment team and your Recruiter will help you throughout different stages. Got any burning questions before then? Drop us a message at talent@octoenergy.com and we&rsquo;d love to help!</div><div></div><div><i><br>
Are you ready for a career with us? We want to ensure you have all the tools and environment you need to unleash your potential. Need any specific accommodations? Whether you require specific accommodations or have a unique preference, let us know, and we'll do what we can to customise your interview process for comfort and maximum magic!</i></div><div></div><div><i><br>
Studies have shown that some groups of people, like women, are less likely to apply to a role unless they meet 100% of the job requirements. Whoever you are, if you like one of our jobs, we encourage you to apply as you might just be the candidate we hire. Across Octopus, we're looking for genuinely decent people who are honest and empathetic. Our people are our strongest asset and the unique skills and perspectives people bring to the team are the driving force of our success. As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. Our commitment is to provide equal opportunities, an inclusive work environment, and fairness for everyone.</i></div>
<p>
Where necessary, we sometimes use AI tools to help with parts of our hiring process, like reviewing applications or assessing responses. We&rsquo;re lucky to receive a huge amount of interest, so these tools help our recruiters manage that volume, not replace them. Ultimately, every hiring decision (for example, whether to progress your application or not) is always made by a real person in our Talent team. If you&rsquo;d like to know more about how we use your data, you can reach out to us via email at talent@octoenergy.com. We&rsquo;re happy to help!</p></div>

Capgemini

<div><div><div><div><p><b>Job Title</b>: Generative AI Engineer/Data Scientist</p>
<p><b>Location</b>: London</p><br>
<p><br>
<b>About the Job you are considering:
</b></p><p>We are seeking a Senior Generative AI Data Engineer with strong experience in financial services (banking, capital markets, insurance, or fintech) to design, build, and scale GenAI-powered data solutions. The role combines modern data engineering, ML/LLM integration, and domain-specific financial knowledge to deliver enterprise-grade AI platforms.<br>
<br>
</p><p><b>Hybrid working:
</b></p><p>The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.</p><br>
<p><br>
<b>Your Role:
</b></p><ul><li>Implement and finetune generative AI models under the guidance of senior team members</li>
<li>Contribute to prompt engineering and development of Ai powered workflows</li>
<li>Assist with the deployment monitoring and maintenance of AI models in production environments</li>
<li>Collaborate with data scientists and engineers to ensure seamless integration of AI capabilities</li>
<li>Perform data preprocessing feature engineering and API development for AI applications</li>
<li>Participate in code reviews testing and documentation to ensure quality and reliability</li>
<li>Stay updated with advancements in GenAI and share relevant learnings with the team</li>
<li>You will lead the development of data pipelines, vector databases, retrieval systems, and LLM-driven applications to solve use cases such as risk analytics, fraud detection, regulatory compliance, document intelligence, and customer insights</li><br>
</ul><p><br>
<b>Your Skills
</b></p><ul><li>Handson experience with at least one major machine learning framework PyTorch TensorFlow Keras</li>
<li>Familiarity with LLMs prompt engineering and finetuning eg LoRA QLoRA</li>
<li>Exposure to RAG systems and basic knowledge of hybrid search techniques</li>
<li>Understanding of model deployment and containerization Docker</li>
<li>Proficiency in Python for AI development data preprocessing and scripting</li>
<li>Experience with generative AI tools LangChain Hugging Face LlamaIndex is a plus</li>
<li>Understanding of version control systems Git</li>
Awareness of AI compliance data privacy and responsible AI principles.<br>
<li>
<br>
</li></ul><p><b>We are a Disability Confident Employer:</b></p>
<p>Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government&rsquo;s Disability Confident scheme.<i> </i>As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who:</p>
<ul><li>Declare they have a disability, and</li>
<li>Meet the minimum essential criteria for the role.</li>
</ul><p>Please opt in during the application process.</p>
<p><b>Make It Real (what does it mean for you):</b></p>
<ul><li>You&rsquo;d be joining an accredited Great Place to work for Wellbeing in 2024. Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce a critical component for us to achieve our organisational ambitions.
<br>
To help support wellbeing we have trained &lsquo;Mental Health Champions&rsquo; across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy.</li>
<li>You will be empowered to explore, innovate, and progress. You will benefit from Capgemini&rsquo;s &lsquo;learning for life&rsquo; mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard ManageMentor, Cybersecurity qualifications and much more.</li>
<li>You will be joining one of the World&rsquo;s Most Ethical Companies&reg;, as recognised by Ethisphere&reg; for 13 consecutive years. We live our values by making ethical business choices every day. Working ethically is at the centre of our culture at Capgemini, meaning you will be helping to create a future we can all be proud of.</li><br>
</ul><p><br>
<b>Why you should consider Capgemini:
</b></p><p>Growing clients&rsquo; businesses while building a more sustainable, more inclusive future is a tough ask. When you join Capgemini, you&rsquo;ll join a thriving company and become part of a collective of free-thinkers, entrepreneurs and industry experts. We find new ways technology can help us reimagine what&rsquo;s possible. It&rsquo;s why, together, we seek out opportunities that will transform the world&rsquo;s leading businesses, and it&rsquo;s how you&rsquo;ll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge, and always pushing yourself to do better, you&rsquo;ll build the skills you want. You&rsquo;ll use your skills to help our clients leverage technology to innovate and grow their business. So, it might not always be easy, but making the world a better place rarely is.</p><br>
<p><br>
<b>About Capgemini:
</b></p><p>Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organisations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of &euro;22.1 billion.
<br>
Make it real | www.capgemini.com</p></div></div></div></div><div></div>

Senior Generative AI Engineer

comply

<div><div><b>Who Are We:</b></div><div></div><div><b><br>
Comply</b> is the leading provider of compliance SaaS and consulting services for the global financial services sector. With more than 5,000 clients and hundreds of employees across the globe, Comply empowers Chief Compliance Officers and their teams to proactively manage regulatory obligations, mitigate risk, and scale with efficiency and confidence.</div><div></div><div><b><br>
Comply </b>serves thousands of global financial services clients including broker-dealers, insurers, investment banks, private funds, RIAs, and wealth managers who rely on Comply offerings to power their compliance programs.</div><div></div><div><br>
To learn more about Comply, visit comply.com</div><div></div><div><b><br>
The Role:</b></div>
<div></div>
<div>We are looking for Senior AI Data Engineers to implement and operationalize Comply&rsquo;s semantic layer &mdash; turning the ontological models defined by our ontologist and architects into working knowledge graphs, vector search infrastructure, and LLM-powered pipelines. This is a hands-on engineering role at the intersection of knowledge representation, AI infrastructure, and data platform engineering. You will own the delivery of semantic layer components, collaborate closely with application and data engineering teams, and ensure that AI-ready data products are reliable, performant, and adopted in practice. You will report into the Data and Analytics organization as part of a new team being created to enable future data capabilities in relation to our AI ambitions.</div>
<h3 class="jobSectionHeader"><b>Responsibilities:
</b></h3><div>Semantic Layer Implementation</div>
<ul><li>Implement JSON-LD-based semantic models designed by the ontologist into production data systems</li>
<li>Build and maintain knowledge graph structures that reflect canonical domain models &bull; Develop and manage graph database schemas, queries, and data ingestion pipelines</li>
<li>Ensure semantic consistency between ontology definitions and downstream data product</li>
</ul><div>AI &amp; Vector Infrastructure</div>
<ul><li>Design and implement embedding pipelines that represent Comply&rsquo;s financial and regulatory data in<br>
vector space</li>
<li>Build and operate vector database infrastructure for semantic search and similarity retrieval</li>
<li>Implement RAG (Retrieval-Augmented Generation) architectures that ground LLM outputs in Comply&rsquo;s<br>
proprietary data</li>
<li>Evaluate and integrate LLM tooling and frameworks appropriate to Comply&rsquo;s use cases</li>
</ul><div>Data Pipeline &amp; Platform Engineering</div>
<ul><li>Build reliable, observable data pipelines that feed the semantic layer from upstream broker and<br>
regulatory data sources</li>
<li>Apply DataOps practices including testing, monitoring, lineage tracking, and SLAs</li>
<li>Work with Data Engineers and Backend Engineers to embed semantic models into APIs and data contracts</li>
<li>Ensure the semantic layer scales with data volume and platform growth</li>
</ul><div>Collaboration &amp; Enablement</div>
<ul><li>Partner closely with the Ontologist to ensure implemented models faithfully reflect domain intent</li>
<li>Support consuming application teams in understanding and adopting AI-ready data products</li>
<li>Contribute to resolving cross-domain data integration challenges</li>
</ul><h3 class="jobSectionHeader"><b>Skills and Qualifications:
</b></h3><ul><li>Strong hands-on experience in data engineering, with a focus on semantic or AI data infrastructure</li>
<li>Experience building and operating knowledge graphs or graph databases (e.g. Jena Fuseki, Neo4j, Amazon<br>
Neptune, or equivalent)</li>
<li>Experience with vector databases and embedding pipelines (e.g. Pinecone, Weaviate, Qdrant, pgvector)</li>
<li>Practical experience implementing RAG architectures or LLM-integrated data pipelines</li>
<li>Familiarity with semantic web standards &mdash; JSON-LD, RDF, OWL, or SKOS</li>
<li>Strong Python skills and experience with data pipeline frameworks</li>
<li>Experience with cloud-native data platforms (AWS, Azure, or GCP)</li>
<li>Exposure to domain-driven design (DDD) and bounded contexts is desirable.</li>
<li>Experience working directly with ontologists or knowledge engineers is a plus.</li>
<li>Familiarity with data contracts and data product frameworks is a plus.</li>
<li>Experience with DataOps tooling, data reliability, or data observability platforms is desirable.</li>
<li>Background in financial services, RegTech, or compliance data is a plus.</li>
</ul><div><b>To learn more about our values, mission and the wide-range of perks offered to employees at Comply, visit </b><b>https://www.comply.com/careers/</b><b>.<br>
</b></div><div></div><br>
<div>Comply is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity, or national origin. Nothing in this job posting should be construed as an offer or guarantee of employment.</div><div>
</div><div>
Applicants must be authorized to work for any employer in the United Kingdom. Currently, we are unable to sponsor or take over sponsorship of an employment Visa at this time.</div><div>
</div><div>
Comply is aware of scammers posing as Comply employees and extending job offers via direct messaging, texts and social media platforms. These are fraudulent and should be treated as such. To learn more about this, please review our Statement of Fraudulent Job Offers.</div><div></div><p><br>
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</p></div>

Senior AI Data Engineer

Bloomberg

<div>
 Location
 <br/>
 <br/>
 London
 <br/>
 <br/>
 Business Area
 <br/>
 <br/>
 Engineering and CTO
 <br/>
 <br/>
 Ref #
 <br/>
 <br/>
 10049302
 <br/>
 <br/>
 <strong>
  Description &amp; Requirements
  <br/>
  <br/>
 </strong>
 Bloomberg&rsquo;s Engineering AI department has 400+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products. At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.
 <br/>
 <br/>
 Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions.
 <br/>
 <br/>
 Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.
 <br/>
 <br/>
 We are looking for Senior ML Platform Engineers with strong expertise and passion for building platforms for (Gen) AI applications.
 <br/>
 <br/>
 As a Senior ML Platform Engineer, you will have the opportunity to create a more cohesive, integrated, and managed AI development life cycle to enable the building and maintenance of our AI systems. Our teams make extensive use of open source technologies such as, Kubernetes, Kubeflow, KServe, Argo, Buildpacks, and other cloud-native MLOps technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source.
 <br/>
 <br/>
 <strong>
  Join the AI Group as a Senior ML Platform Engineer and you will have the opportunity to:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Architect, build, and diagnose multi-tenant AI platform systems
  </li>
  <li>
   Work closely with AI application teams to design seamless workflows for continuous model training, inference, and monitoring
  </li>
  <li>
   Work with AI experts to understand workflows, pinpoint, and resolve inefficiencies, and to inform the next set of features for the platforms
  </li>
  <li>
   Collaborate with open-source communities and AI application teams to build a cohesive MLOps experience
  </li>
  <li>
   Design CI/CD automation frameworks that incorporate regulatory requirements
  </li>
  <li>
   Develop cloud-native deployment patterns for AI systems across environments
  </li>
  <li>
   Troubleshoot and debug user issues
  </li>
  <li>
   Provide operational and user-facing documentation
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  We are looking for a Senior ML Platform Engineer with:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Proven years of experience working with an object-oriented programming language (Python, Go, etc.)
  </li>
  <li>
   Experience designing cloud-native, distributed platforms
  </li>
  <li>
   Strong knowledge of Kubernetes, Argo, and container orchestration technologies
  </li>
  <li>
   Previous experience with modern CI/CD tools and GitOps workflows
  </li>
  <li>
   Familiarity with implementing automation for model development lifecycles
  </li>
  <li>
   A proactive mentality and ability to collaborate with peers, stakeholders, and management
  </li>
  <li>
   A Degree in Computer Science, Engineering, Mathematics, or similar field of study or equivalent work experience
  </li>
  <li>
   An understanding of Computer Science fundamentals such as data structures and algorithms
   <br/>
   <br/>
  </li>
 </ul>
 We give back to the technology community and you can read more about our outreach at:
 <br/>
 <br/>
 If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
 <br/>
 <br/>
 Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.
</div>


Senior ML Platform Engineer - Artificial Intelligence

Ciklum

<p></p><div><div><div><div><div><div><div><div><div><div><div><b>Ciklum</b> is looking for a <b>Expert Agentic AI Engineer</b> to join our team full-time in the UK .<br>
We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live.</div><p><b>
About the role:</b></p><p>
As a Expert Agentic AI Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.</p><p><b>
Responsibilities:</b></p><ul><li>
Design, build, train, and deploy production-grade Machine Learning, Deep Learning, or Natural Language Processing (NLP) models</li><li>
Optimize ML models for enterprise-scale latency, throughput, and performance, ensuring flawless integration with data warehouses and automated workflow bots</li><li>
Partner with Data Engineers to engineer high-quality data pipelines, automated feature stores, and secure data preprocessing routines</li><li>
Establish and scale MLOps workflows to handle model lineage tracking, code versioning, automated validation gates, and continuous deployment pipelines</li><li>
Set the core technical direction for AI engineering across squads, evaluate emerging AI methodologies, and provide high-level mentorship to senior team members</li></ul><p><b>
Requirements:</b></p><ul><li>
5+ years (Senior) or 8+ years (Expert) of professional experience developing, shipping, and maintaining machine learning models in live production environments</li><li>
Agentic Frameworks: Hands-on experience building autonomous workflows, custom plugins, and orchestration logic using Microsoft Copilot Studio or semantic kernels</li><li>
Cloud AI Infrastructure: Proven experience deploying and fine-tuning generative AI models, prompt flow, and vector databases within Azure AI Foundry (formerly Azure AI Studio)</li><li>
Tool Integration: Strong background in connecting LLMs to external APIs, enterprise data sources, and robotic process automation (RPA) tools to enable autonomous action execution</li><li>
Elite proficiency in Python paired with extensive experience using core ML libraries and frameworks (such as PyTorch, TensorFlow, Scikit-Learn, or Hugging Face)</li><li>
Hands-on experience working with MLOps tracking tools and cloud-based AI infrastructure ecosystems (such as MLflow, Kubeflow, AWS SageMaker, or Azure ML)</li><li>
Strong computer science fundamentals, including advanced knowledge of data structures, algorithmic complexity, and clean code principles. a formal degree in Computer Science, Data Science, Mathematics, or a highly quantitative field is strongly preferred</li></ul><p><b>
What`s in it for you?</b></p><ul><li>
Strong community: Work alongside top professionals in a friendly, open-door environment</li><li>
Growth focus: Take on large-scale projects with a global impact and expand your expertise</li><li>
Tailored learning: Boost your skills with internal events (meetups, conferences, workshops), Udemy access, language courses, and company-paid certifications</li><li>
Endless opportunities: Explore diverse domains through internal mobility, finding the best fit to gain hands-on experience with cutting-edge technologies</li><li>
Care: Healthcare, Basic Life Insurance, Short and Long-term disability insurance according to the Company&rsquo;s Benefit Plans</li></ul><p><b>
About us:</b></p><p>
At Ciklum, we are always exploring innovations, empowering each other to achieve more, and engineering solutions that matter. With us, you&rsquo;ll work with cutting-edge technologies, contribute to impactful projects, and be part of a One Team culture that values collaboration and progress. In the UK, Ciklum is growing fast&mdash;inviting experienced professionals to lead digital transformation alongside Fortune 500 clients. Be part of a company where innovation and impact go hand in hand.</p><p><b>
Explore, empower, engineer with Ciklum!</b></p><p>
Interested already? We would love to get to know you! Submit your application. We can&rsquo;t wait to see you at Ciklum.</p><p>
#LI-VH1</p></div>
</div></div></div></div></div></div><div></div><div><div><div><div><div><div><p>REQUIRED SKILLS</p>
<div><ul><p>Agentic AI</p>
</ul></div></div></div></div></div></div></div><div></div><div><div><div><div><div><div><div>
</div></div></div></div></div></div></div><div><div><div><div><div><div><p>JOB INFO</p>
<div><div><div><ul><div><div>Job Identification</div>
<div>3619</div>
</div><div><div>Job Category</div>
<div>Intelligent Automation</div>
</div><div><div>Posting Date</div>
<div>07/03/2026, 02:34 AM</div>
</div><div><div>Locations</div>
<div> <div></div><div><div>London
</div></div>(Hybrid)</div></div></ul></div></div></div></div></div></div></div></div></div></div></div></div><p></p>

Expert Agentic AI Engineer

Accenture

<div><p><b>YOU ARE</b></p><p>
As a hands-on Infrastructure architect, you are an early-career engineer who learns and grows while contributing hands-on to the AI and machine learning infrastructure that powers real-world applications. Under the guidance of senior architects and engineers, you'll develop practical skills in coding, testing, configuring, deploying, monitoring, and troubleshooting AI systems and the infrastructure they run on. Day to day, you'll write and test code and deployment scripts, help configure cloud and on-premises compute resources such as GPU clusters and distributed training environments, deploy AI systems and models into production, and support data pipelines that feed AI and ML workflows. You'll learn to monitor AI systems and infrastructure health across both InfraOps and MLOps disciplines, perform AI monitoring to track model and system performance, and troubleshoot issues across the computational stack with mentorship and support. This is a hands-on, learning-focused where you build expertise across modern tools and platforms &mdash; including container orchestration, model serving, CI/CD pipelines, InfraOps, MLOps, and AI monitoring &mdash; while making meaningful contributions to infrastructure that enables AI-driven busin</p><p>
ess outcomes.</p><p></p><p><b>
THE WORK</b></p><ul><li>
Write, test, and debug code and scripts for AI infrastructure tasks, including automation and tooling, under the guidance of senior engineers.</li><li>
Develop and maintain infrastructure and software deployment scripts to support reliable, repeatable releases of AI systems and models.</li><li>
Configure and provision compute resources across cloud and on-premises environments, including GPU clusters and distributed training setups.</li><li>
Deploy AI systems and machine learning models into production infrastructure, following established processes and best practices.</li><li>
Deploy data pipelines that feed AI and ML workflows, ensuring data is available, clean, and reliable.</li><li>
Assist with container orchestration and model serving, learning tools such as Docker, Kubernetes, and model deployment frameworks.</li><li>
Support and maintain CI/CD pipelines for automating the build, test, and deployment of AI infrastructure and applications.</li><li>
Monitor AI systems and infrastructure health across InfraOps and MLOps disciplines, tracking performance, reliability, and resource utilization.</li><li>
Perform AI monitoring to track model performance, detect drift or degradation, and surface issues for review.</li><li>
Troubleshoot and help resolve issues across the computational stack &mdash; hardware, networking, software, and models &mdash; with mentorship and support.</li><li>
Document configurations, processes, and procedures to maintain clear, repeatable, and shareable knowledge across the team.</li><li>
Collaborate with senior architects and engineers, participating in code reviews, team discussions, and knowledge-sharing sessions to grow technical skills.</li><li>
Apply security, cost-efficiency, and scalability best practices as you learn them, contributing to well-managed and responsible infrastructure.</li></ul></div>
<br>
<div><p><b>EDUCATION</b></p><ul><li>
Bachelor's Degree in Computer Science, Computer Engineering, related Engineering field</li></ul><p></p><p><b>
BASIC (REQUIRED) QUALIFICATION</b></p><ul><li>
Work or coursework experience with AI/ML or Computer engineering or Computer science.</li><li>
Coding, building, monitoring, troubleshooting applications of AI/ML models; selecting, designing and infrastructure for deploying and running them on premise or on public cloud.</li><li>
Strong understanding of AI and machine learning as a subject.</li><li>
Strong understanding of computing infrastructure a subject, preferred knowledge of AI infrastructure.</li><li>
Proficiency in programming languages such as Python, Java, or C++.</li></ul></div><p></p>

AI Infrastructure Architecture Analyst

Explore 338+ Senior ai engineer in London this July. Find roles across top companies and apply now to boost your career.

338 senior ai engineer jobs In London

Senior AI Engineer

Senior AI Engineer

Senior Generative AI Engineer

Senior AI Data Engineer

Senior ML Platform Engineer - Artificial Intelligence

Expert Agentic AI Engineer

AI Infrastructure Architecture Analyst