ai data 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

Deloitte

<div><div><div><div><h3 class="jobSectionHeader"><b>Basic information
</b></h3></div></div><div><div><div><div>Location
</div><div>London
</div></div><div><div>Business Line
</div><div>Tax &amp; Legal
</div></div><div><div>Job Type
</div><div>Contract
</div></div><div><div>Date published
</div><div>29-Jun-2026
</div></div><div><div>Req #
</div><div>23837
</div></div></div></div></div><div><div><div><h3 class="jobSectionHeader"><b>Job description
</b></h3></div></div><div></div><div><div><div><div><p><b>Job Title:</b> AI Data Engineer (Azure)</p><p><b>
Location: </b>London Hybrid. Travel to the London office 2 days a week</p><p><b>
Duration: </b>6 months</p><p><b>
Contract Start Date:</b> ASAP</p><p><b>
Day rate:</b> Competitive (Inside IR35)</p><p></p><p><b><br>
Deloitte</b></p><p>
Working with the Deloitte Associate (Contractor) Programme means we can offer you the opportunity to work on a variation of industry and client related projects. Our aim is to retain the best talent and so when your project end date nears our team of Talent Community Advisors will be working with you to look at alternative projects within the firm that suit your experience should you wish to continue with Deloitte.</p><p></p><p><b><br>
The Role</b></p><p>
We are looking for a highly skilled <b>AI Data Engineer </b>(Contractor) specialising in <b>Azure </b>to join our Digital Innovation team, supporting cutting-edge data and analytics use cases across Tax &amp; Legal. This role is ideal for someone who combines <b>strong </b><b>AI/GenAI data pipeline</b><b> </b>expertise with <b>hands-on Azure, data discovery and analysis. </b>You will be comfortable working with unstructured data and modern Azure-native architectures. You will play a key role in transforming complex datasets into meaningful insights, working closely with Tax domain specialists to understand requirements, shape solutions, and clearly present outputs that drive business value. We're looking for a strong communicator with problem solving skills who can bridge technical data engineering and business understanding. A proactive, delivery-focused engineers who is comfortable working at pace.</p><p></p><p><b><br>
Deliverables: Responsibilities but not limited to:</b></p><b>
1. Data Engineering &amp; Azure Platform Delivery</b><br>
<ul><li><ul><li>
Design and build end-to-end data pipelines using Azure (ADF, Synapse, Fabric)</li><li>
Develop scalable frameworks for ingesting structured, semi-structured, and unstructured data</li><li>
Implement modern architectures (e.g. Lakehouse, medallion &ndash; bronze/silver/gold)</li><li>
Build and optimise storage solutions across ADLS Gen2, Cosmos DB, and Azure SQL/Synapse</li><li>
Deliver scalable, maintainable, production-ready solutions</li></ul></li></ul><b>
2. Unstructured Data &amp; NoSQL Engineering</b><ul><li><ul><li>
Design pipelines to process, transform, and enrich unstructured data.</li><li>
Leverage Cosmos DB for high-throughput, low-latency, schema-flexible workloads</li><li>
Optimise partitioning, indexing, and query performance</li><li>
Enable downstream analytics and AI use cases (e.g. reporting, search, RAG)</li></ul></li></ul><b>
3. Data Discovery, Analysis &amp; Business Engagement</b><ul><li><ul><li>
Conduct data discovery, profiling, and exploratory analysis</li><li>
Collaborate with Tax &amp; Legal stakeholders to translate business needs into data solutions</li><li>
Identify trends, anomalies, and data quality issues</li><li>
Present insights clearly to non-technical and senior stakeholders</li><li>
Support development of curated datasets and semantic layers</li></ul></li></ul>
4. <b>Collaboration &amp; Delivery</b><ul><li><ul><li>
Work with data scientists, AI engineers, architects, and domain specialists</li><li>
Enable data consumption via reporting tools, APIs, and data services</li><li>
Contribute to best practices in governance, lineage, and data cataloguing</li><li>
Deliver high-quality solutions in agile environments</li></ul></li></ul><p></p><p><b><br>
Essential Skills and Experience</b></p><ul><li><ul><li>
Proven experience as an <b>Azure Data Engineer </b>in end-to-end data platforms</li><li>
Exposure to <b>AI/GenAI data pipelines </b>(e.g. RAG, embeddings, search)</li><li>
Knowledge of <b>Azure AI Search</b> or vector-based retrieval systems</li><li>
Strong <b>hands-on</b> experience with:</li><li><ul><li><ul><li>
Azure Data Factory / Synapse / Microsoft Fabric</li><li>
Azure Data Lake Storage (ADLS Gen2)</li><li>
Azure Cosmos DB (Core/SQL API, NoSQL modelling)</li></ul></li></ul></li><li>
Experience working extensively with unstructured and semi-structured data</li><li>
Proficiency in <b>Python</b> and <b>SQL</b></li><li>
Demonstrated experience in:</li><li><ul><li><ul><li>
Data discovery, profiling, and exploratory analysis</li><li>
Data transformation and data quality frameworks</li></ul></li></ul></li><li>
Strong understanding of:</li><li><ul><li><ul><li>
NoSQL vs relational data modelling</li><li>
Data partitioning and performance tuning</li></ul></li></ul></li><li>
Experience building scalable, production-grade data pipelines</li><li>
Familiarity with CI/CD and DevOps practices in Azure</li></ul></li></ul><p></p><p><b><br>
Desirable:</b></p><ul><li><ul><li>
Azure Data Engineering Associate certification (DP-203) or equivalent</li><li>
Experience with Microsoft Fabric and Lakehouse architectures</li><li>
Experience integrating Cosmos DB with analytical platforms</li><li>
Familiarity with data governance frameworks</li></ul></li></ul><p></p><p><b><br>
IR35</b></p><p>
As a means of managing tax, commercial and reputational risks, Deloitte prohibits the use of Associates through Personal Service Companies (&lsquo;PSCs&rsquo;). All Associates must contract under PAYE arrangements through a Deloitte approved &lsquo;Employment Company&rsquo; (aka &lsquo;umbrella company.&rsquo;)</p></div></div></div></div></div></div><div></div>

Contract - AI Data Engineer (Azure)

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

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

Athsai

<div>
 <p>
  **Employment Type:** Permanent
 </p>
 <p>
  **Salary:** Up to &pound;75k
 </p>
 <p>
  **Location:**
  <strong>
   <em>
    in the Central London
   </em>
  </strong>
 </p>
 <p>
  <strong>
   **Work Arrangement:** In-office only, five days a week.
  </strong>
 </p>
 <p>
  ---
 </p>
 <p>
  <br/>
 </p>
 <p>
  **Job Title:** Data Engineer
 </p>
 <p>
  <br/>
 </p>
 <p>
  **Experience Required:** 8 Years
 </p>
 <p>
  <br/>
 </p>
 <p>
  **Role Overview:**
 </p>
 <p>
  <br/>
 </p>
 <p>
  We are seeking a Data Engineer to design and implement scalable data solutions, including real-time and ETL/ELT data pipelines. Responsibilities include optimizing our data warehouse, creating Power BI reports, and developing AI-driven solutions using OpenAI APIs.
 </p>
 <p>
  <br/>
 </p>
 <p>
  **Key Responsibilities:**
 </p>
 <p>
  <br/>
 </p>
 <p>
  - Design and implement robust real-time data pipelines from diverse sources.
 </p>
 <p>
  - Maintain a high-performance data warehouse for reporting and analytics.
 </p>
 <p>
  - Develop insightful Power BI dashboards and reports for stakeholders.
 </p>
 <p>
  - Use Azure Data Factory, Azure Functions, and Logic Apps for data integration.
 </p>
 <p>
  - Employ Python and SQL for data transformation and analysis.
 </p>
 <p>
  - Leverage OpenAI APIs for AI/ML solutions.
 </p>
 <p>
  - Collaborate with teams to align data strategy with business goals.
 </p>
 <p>
  - Ensure data quality, consistency, and compliance.
 </p>
 <p>
  <br/>
 </p>
 <p>
  **Required Qualifications:**
 </p>
 <p>
  <br/>
 </p>
 <p>
  - 7-8 years in Data Engineering, Data Architecture, or related roles.
 </p>
 <p>
  - Experience with ETL/ELT pipelines and complex data ecosystems.
 </p>
 <p>
  - Proficiency in Python and strong SQL skills.
 </p>
 <p>
  - Familiarity wit
  <strong>
   h Azure services (Data Factory, Logic Apps, etc.).
  </strong>
 </p>
 <p>
  - Expertise in Power BI for data modeling and visualization.
 </p>
 <p>
  - Experience with OpenAI APIs or similar services.
 </p>
 <p>
  - Understanding of data warehousing and data governance.
 </p>
 <p>
  <br/>
 </p>
 <p>
  **Preferred Qualifications:**
 </p>
 <p>
  <br/>
 </p>
 <p>
  - Knowledge of DevOps practices and CI/CD pipelines.
 </p>
 <p>
  - Familiarity with cloud-native data platforms (e.g., Databricks).
 </p>
 <p>
  - Understanding of data privacy regulations (e.g., GDPR).
 </p>
</div>


Data Engineer - Azure/ADF

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

Houseful

<div><p><b><i>6 months Initial Contract - Must work from the UK</i></b></p><p>
Alto Software Group (ASG) is a leading B2B SaaS platform serving the UK property industry. We power thousands of estate agency branches and support a significant proportion of UK housing transactions each year.</p><p>
We are building a data-driven, operationally efficient platform business. AI will be a structural lever in improving internal productivity, reducing operational cost, and enhancing customer experience.</p><p>
This is a hands-on delivery role responsible for building the automations and AI integrations that embed AI into how we operate.</p>
The Role<p>
We are hiring a contract AI Engineer to build, deploy and maintain AI-enabled automations across our core systems stack. Working with the Principal Engineer and the Head of AI Operations, you will take prioritised automation opportunities from design through to production.</p><p>
You will deliver against an internal AI roadmap spanning Customer Operations, Marketing, Finance, Education and Training to:</p><ul><li>Automate high-volume, manual administrative workflows</li><li>Build AI-enabled workflows in Salesforce, Zendesk, HubSpot, Zuora and Thrive LMS</li><li>Turn the Mission Control data platform into an engine for event-triggered automation</li><li>Reduce operational overhead and improve reporting speed and accuracy</li></ul>
Core ResponsibilitiesAutomation Build &amp; Integration<ul><li>Build and maintain automation pipelines using n8n, Zapier/Make and direct LLM API integrations (OpenAI/Anthropic)</li><li>Develop API and webhook integrations across Salesforce, Zendesk, HubSpot, Zuora and Thrive LMS</li><li>Implement workflows such as ticket summarisation, tagging, routing and AI triage</li></ul>
AI Engineering<ul><li>Design and implement RAG pipelines and vector database integrations over internal knowledge</li><li>Develop, test and version prompts; evaluate and improve output quality</li><li>Build event-triggered automations and AI-enabled reporting on Mission Control</li></ul>
Quality, Security &amp; Handover<ul><li>Apply sound engineering standards: error handling, logging and monitoring of automations in production</li><li>Ensure GDPR-compliant, secure handling of customer and company data</li><li>Document solutions clearly and hand over to internal teams for ongoing operation</li></ul>
What Success Looks Like (First 6 Months)<ul><li>Priority automation workflows live, stable and monitored in production</li><li>Measurable reduction in manual effort in targeted workflows</li><li>Reliable integrations across the core systems stack</li><li>Clear documentation enabling internal teams to operate and extend what you build</li></ul>
Required ExperienceTechnical<ul><li>Proven delivery of LLM-based automation in production environments</li><li>Strong experience with automation platforms (n8n, Make or Zapier)</li><li>Proficiency in Python and SQL</li><li>Strong API and webhook integration capability</li><li>Experience working with OpenAI/Anthropic APIs and prompt engineering</li><li>Experience building RAG pipelines and working with vector databases</li><li>Experience automating CRM (Salesforce) and support (Zendesk) environments preferred</li></ul>
Delivery<ul><li>Experience operating in B2B SaaS or similar fast-moving environments</li><li>Track record of delivering as a contractor: scoping, building and handing over cleanly</li><li>Comfortable working with non-technical stakeholders to refine requirements</li></ul>
Personal Attributes<ul><li>Delivery-focused and pragmatic</li><li>High agency and accountability</li><li>Structured, with strong attention to reliability and security</li><li>Comfortable working in ambiguity</li><li>Clear communicator with technical and non-technical audiences</li></ul>
Why This Role Matters<p>
AI will be a structural margin lever for ASG. The automations you build will directly reduce operational cost, increase capacity without incremental headcount, and embed AI as core operational infrastructure rather than experimentation.</p></div>

AI Engineer (Contract)

Explore 361+ Ai data engineer in London this July. Find roles across top companies and apply now to boost your career.