ai solutions engineer

Lorien

<div>
 
 AI Solutions Engineer / Applied AI Engineer
 
 
 Location: London (Hybrid) 3 days onsite
 
 
 Perm
 
 
 Cheapside, London EC2V 6EE
 
 
 
 
 
 Criteria:
 
 
 &bull; AI-Native Engineering Practice
 
 
 &bull; Software Engineering Experience
 
 
 &bull; Databricks and Python Proficiency
 
 
 &bull; Functional Empathy and Stakeholder Engagement
 
 
 &bull; Solution Ownership and Quality
 
 
 
 
 
 We&rsquo;re looking for engineers who are not only deeply technical in AI but also excellent communicators and stakeholder partners.
 
 
 
 
 
 Some engineers love technology for technology&rsquo;s sake. This role is different. At HeadFirst x Impellam, we&rsquo;re looking for someone who enjoys figuring things out, understands how organizations work, and gets a kick out of building solutions that genuinely improve the day-to-day reality of teams across the business.
 
 
 
 
 
 As an Applied AI Engineer, you work directly with departments such as Finance, HR, Sales, and Marketing to streamline processes, eliminate friction, and help people work smarter through AI, automation, and lightweight internal applications. You aren&rsquo;t expected to be an expert in every framework, platform, or tool from day one. What matters more is how you think, how quickly you learn, and how effectively you turn ambiguity into practical results.
 
 
 This is a high-profile role that makes a real difference to the business. You&rsquo;ll spend just as much time understanding workflows, challenging assumptions, and shaping solutions as you do building them. The people who thrive here are curious, pragmatic, and comfortable working closely with stakeholders rather than hiding behind tickets or isolated engineering backlogs.
 
 
 Your impact
 
 
 
 
 
 As an Applied AI Engineer, you&rsquo;ll serve as a consultant, a builder, and a problem solver all in one. You&rsquo;ll work closely with business teams to understand how work actually gets done. Sometimes the challenge is operational inefficiency. Sometimes it&rsquo;s fragmented tools, repetitive manual work, or slow decision-making caused by disconnected systems and unclear information flows.
 
 
 Your role is to identify where AI, automation, or lightweight applications can deliver immediate value, and then help bring that value to life quickly and pragmatically. Rather than spending months designing perfect systems, you focus on delivering usable solutions quickly, gathering feedback early, and improving continuously. This could involve building an internal workflow tool, creating an AI-powered assistant for operational teams, or streamlining reporting and approvals through automation.
 
 
 
 
 
 You work within a modern Databricks and AI-enabled ecosystem, but technology is never the end goal. The real objective is to help teams operate more effectively, make better decisions, and eliminate operational bottlenecks. AI plays a central role in how you work. AI coding assistants and agent-based workflows help accelerate development and experimentation, allowing you to move quickly while still maintaining control over quality, usability, and adoption.
 
 
 At the same time, you work closely with the Platform, Data, and Engineering teams to ensure that the solutions you deliver fit within a scalable and secure organizational environment.
 
 
 
 
 
 What you will do
 
 
 &bull; Work closely with business stakeholders to understand operational challenges, workflows, and inefficiencies;
 
 
 &bull; Translate ideas and business needs into practical tools, automations, and AI-powered solutions;
 
 
 &bull; Build lightweight internal applications that boost productivity and simplify daily work;
 
 
 &bull; Use AI coding assistants and AI-native workflows to speed up delivery and experimentation;
 
 
 &bull; Continuously refine solutions based on real user feedback and adoption;
 
 
 &bull; Support teams in improving processes rather than simply digitizing existing inefficiencies;
 
 
 &bull; Collaborate with Finance, HR, Commercial, and leadership teams on business-critical initiatives;
 
 
 &bull; Balance speed and quality by making pragmatic engineering decisions that maintain momentum;
 
 
 &bull; Introduce smarter workflows through automation, AI agents, and integrated internal tools;
 
 
 &bull; Help shape how AI is adopted responsibly and practically throughout the organization;
 
 
 &bull; Share ideas, best practices, and suggestions for improvement that help teams move faster and work more effectively.
 
 
 
 
 
 Who you are
 
 
 You&rsquo;re someone who enjoys solving problems in complex, real-world environments. You likely combine technical curiosity with strong communication skills and a genuine interest in how businesses operate. You don&rsquo;t need perfect requirements or fully defined roadmaps to get started. Instead, you ask questions, explore possibilities, and move toward solutions quickly. You&rsquo;re energized by learning new things and comfortable adapting as technology evolves. AI doesn&rsquo;t intimidate you. You see it as a practical tool that helps you think faster, build faster, and create more impact.
 
 
 You enjoy collaborating and are comfortable working closely with non-technical stakeholders. You know how to explain ideas clearly, challenge assumptions constructively, and maintain momentum without overcomplicating things. Most importantly, you care about results. You enjoy delivering useful solutions, seeing people adopt them, and improving them over time based on what works in practice.
 
 
 
 
 
 Why this role stands out
 
 
 This is not a traditional engineering role focused solely on technical implementation. You will work closely with decision-makers, influence how teams operate, and help shape the practical implementation of AI across an international organization. The role combines engineering, consulting, problem-solving, and business collaboration in a way that offers broad exposure and a tangible impact.
 
 
 If you enjoy fast-paced environments, practical innovation, and building solutions that people actually use, this role offers the opportunity to have a direct impact on how modern AI capabilities create value within a global business.
 
</div>

AI Solutions Engineer / Applied AI Engineer

Dentons

<div>
 
 
 Department/Division
 
 : Solutions/Innovation
 
 
 
 Duration
 
 : Permanent
 
 
 
 Type of Role
 
 : Hybrid
 
 
 
 Reference Number
 
 : 10203
 
 
 
 
 
 
 The Team
 
 
 
 
 
 
 The Innovation &amp; AI team sits within the Solutions function and is responsible for identifying, developing and scaling innovative solutions, including AI and legal technology, to enhance client service delivery and internal efficiency.
 
 
 
 
 
 The team works closely with IT, Office of the General Counsel (OGC), Procurement, Solutions/Helix and Practice Groups to pilot, implement and embed new tools and ways of working across the firm.
 
 
 
 
 
 
 The Role
 
 
 
 
 
 
 The Applied AI Engineer designs, builds and productionises AI-enabled solutions for legal and business services delivery. Working consultatively with stakeholders and delivery teams, the role translates use cases into technical designs across Python applications, cloud workflows, enterprise platforms, AI skills, agents, integrations and automations.
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 <ul>
 <li>
 Design, build and maintain AI-enabled applications, automations and internal tools using Python, cloud services and enterprise platforms.
 </li>
 <li>
 Work with stakeholders to understand business problems, assess use cases and translate requirements into practical technical designs.
 </li>
 <li>
 Build integrations between internal systems, enterprise platforms, external applications and AI services.
 </li>
 <li>
 Develop reusable AI skills, agents, workflow components and automation patterns that can be adopted across the firm.
 </li>
 <li>
 Build document-focused AI workflows, including extraction, summarisation, search, retrieval and due diligence support.
 </li>
 <li>
 Productise AI pilots by improving reliability, maintainability, testing, evaluation, documentation and reuse.
 </li>
 <li>
 Design and implement multi-step AI workflows, including tool-using, agentic and platform-native automations where appropriate.
 </li>
 <li>
 Collaborate with product, UX, engineering, cloud, innovation and business teams to deliver secure, production-ready solutions.
 </li>
 <li>
 Apply sound engineering judgement around confidential client data, privacy, security, governance and responsible AI.
 </li>
 </ul>
 
 
 
 
 
 Key Skills &amp; Experience
 
 
 
 
 
 <ul>
 <li>
 Python software engineering experience across applications, integrations, automations or internal tools.
 </li>
 <li>
 Experience building or implementing AI/ML or LLM-enabled solutions in production or near-production settings.
 </li>
 <li>
 Experience working with APIs, SDKs, cloud services and enterprise platforms.
 </li>
 <li>
 Practical understanding of prompt engineering, RAG, LLM workflows or agentic patterns.
 </li>
 <li>
 Ability to interview stakeholders and translate business processes into technical designs.
 </li>
 <li>
 Experience with testing, debugging, documentation, Git and maintaining reliable systems.
 </li>
 <li>
 Strong communication and problem-solving skills across technical and non-technical audiences.
 </li>
 </ul>
 
 
 
 
 
 Preferred:
 
 
 
 
 
 <ul>
 <li>
 Experience within a legal, professional services or other document-intensive enterprise environment.
 </li>
 <li>
 Familiarity with document processing pipelines, unstructured data workflows or knowledge retrieval systems.
 </li>
 <li>
 Experience with orchestration frameworks, agents, skill-building frameworks or workflow automation tools.
 </li>
 <li>
 Experience building on enterprise AI platforms or comparable environments.
 </li>
 <li>
 Exposure to governance, security, privacy and responsible AI considerations in enterprise environments.
 </li>
 </ul>
 
 
 
 
 
 Personal Attributes
 
 
 
 
 
 <ul>
 <li>
 Pragmatic and delivery-focused, with the ability to turn ambiguous ideas into working solutions.
 </li>
 <li>
 Consultative and curious, able to ask good questions and challenge assumptions constructively.
 </li>
 <li>
 Collaborative and comfortable working across multidisciplinary teams.
 </li>
 <li>
 Adaptable in a fast-moving environment where requirements and technologies evolve.
 </li>
 <li>
 Clear communicator who can explain technical concepts to non-technical stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Firm Profile
 
 
 
 Across more than 80 countries, Dentons helps you grow, protect, operate and finance your organisation by providing uniquely global and deeply local legal solutions. Polycentric, purpose-driven and committed to inclusion, diversity, equity and sustainability, we focus on what matters most to you. www.dentons.com
 
 
 
 
 
 
 Inclusion and Diversity
 
 
 
 We are committed to building an inclusive culture here at Dentons where our people can thrive, regardless of their background or circumstance. As well as being the right thing to do, it makes good business sense too. A richness of backgrounds, experiences and perspectives helps us best serve our clients and the communities in which we operate. You can find out more about inclusion and diversity at Dentons here: Inclusion and Diversity
 
 
 
 
 
 Dentons is committed to providing equal opportunities for all. We welcome applications from everyone including of any age, ethnicity, religion, sex, sexual orientation, gender identity, nationality, neurotype, disability, or with parental or caring responsibilities. We are also &ldquo;Happy to Talk Flexible Working&rdquo; and welcome conversations about flexible working arrangements.
 
 
 
 
 
 Dentons is a Disability Confident employer. Candidates with a disability may choose to apply under the Disability Confident Scheme. We will offer an interview to disabled applicants who meet the minimum criteria for the role. Where application volumes are high, we may offer interviews to those who best meet the minimum criteria, consistent with our approach for all candidates.
 
 
 
 
 
 During the application process, all applicants have the opportunity to tell us about any adjustments or support they require so they are able to perform at their best. Any information you share with us during the application process is treated in confidence.
 
 
 
 
 
 If you have any questions about this or the role criteria, please email recruitment.matters@dentons.com.
 
 
 
 
 
 
 NO AGENCIES PLEASE
 
 
 
 If you are interested in applying for this position, we welcome direct applications via our careers page, but if you have any questions beforehand, please email recruitment.matters@dentons.com. Enquiries only please &ndash; applications will not be accepted via email.
 
 
 
 
 
 Please note that we will not accept unsolicited CVs sent to the business, nor will we accept any associated terms of business.
 
</div>

Applied AI Engineer

SQLI

<div>
 
 We Elevate. Digitally.
 
 
 
 
 SQLI is a European leader in digital transformation and customer experience, helping major international brands drive growth through technology. From strategy to implementation, we design and deliver high-performance architectures and engaging digital experiences by combining advanced technologies, proven methodologies, and deep technical expertise.
 
 
 
 
 With 2,200 people across 12 countries, we&rsquo;re looking for passionate individuals who share our values: Creative Spirit, Commitment, and Forward Thinking.
 
 
 
 
 
 
 Job Description
 
 
 
 
 
 
 About the role
 
 
 
 
 
 
 The AI Engineer is the build engine of our AI practice. You turn business requirements into working AI solutions, fast, using coding agents and frontier models, then take the ones that prove their worth into production with the security, compliance, and reliability that enterprise clients demand.
 
 
 
 
 This is not a model-training role. We are not building or fine-tuning models from scratch. You build agentic workflows and LLM-powered applications on top of frontier models, wire them into real enterprise systems, and make them safe to run.
 
 
 
 
 You will work as part of the delivery team alongside consultants, business analysts, and architects. The consultant carries the client relationship and the architect owns the hard architectural calls. You own the build and you make real engineering decisions, not just execute someone else&rsquo;s spec. You are proactive about spotting better ways to build, and trusted to deliver without close supervision.
 
 
 
 
 
 
 What you will do
 
 
 
 
 
 <ul>
 <li>
 
 Use coding agents to prototype AI solutions quickly against real client requirements, so the team can validate value before committing to a full build
 
 
 
 </li>
 <li>
 
 Build, deploy, and maintain LLM-powered applications and agents that align with enterprise architecture principles and standards, with evaluation, monitoring, and token tracking in place from day one
 
 
 
 </li>
 <li>
 
 Set up MCP connectors and permissions against client systems, taking real care over data handling, access control, and what an agent is and is not allowed to do
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Build production solutions that meet client security requirements and European data protection obligations, including GDPR. This is not optional and not an afterthought
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Collaborate with consultants, business analysts, and architects to break business requirements down into solutions that are feasible, maintainable, and safe
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Create reusable AI assets and accelerators for the practice, including skills, plugins, and MCP servers that make future engagements faster
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Support Data &amp; AI teams with best practices around AI-assisted development, documentation, and automation, and coach less experienced colleagues on agentic build patterns and security standards
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Document deployment, upgrade paths, and maintenance so SQLI and our clients can own what you build after handover
 
 
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 
 
 
 <ul>
 <li>
 
 Proven experience with AI-assisted development. You have shipped something real with Claude or another agent platform, not just followed tutorials
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Strong TypeScript and/or Python for agentic glue code, custom MCP work, and evaluation
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience building RAG applications
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Hands-on with creating and using agent plugins, skills, and MCP servers for repeatable agentic workflows
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Skilled at engineering the prompts and context that let agents do work as autonomously as is safe and sensible
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Solid grasp of security, access control, and data protection (including GDPR) when building systems that act against real client data with real permissions
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience setting up CI/CD pipelines and automation
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Able to take a prototype through to a production-grade build, not just one or the other
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Strong collaboration and communication skills, ideally from an agency or consulting setting
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Proactive and autonomous, able to spot opportunities, make sound engineering decisions, and own delivery rather than wait to be told how to build
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Business-level English, able to understand business requirements directly from clients and communicate clearly in calls and in writing
 
 
 
 </li>
 </ul>
 
 
 
 Nice to have
 
 
 
 
 
 <ul>
 <li>
 
 Familiar with Microsoft Azure, particularly Azure AI infrastructure, as our primary cloud for production AI
 
 
 
 </li>
 <li>
 
 Hands-on with Anthropic&rsquo;s managed agent infrastructure (Claude managed agents, the agents API)
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Prior work on evaluation methods for LLM outputs
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Experience in e-commerce, or from an AI, agentic, or workflow automation background
 
 
 
 </li>
 </ul>
 <ul>
 <li>
 
 Comfortable presenting technical work and learnings to a non-engineering audience
 
 
 
 
 
 </li>
 </ul>
 
 Additional Information
 
 
 
 
 
 
 How we will work together
 
 
 
 
 
 
 You will report into the Data &amp; AI service line leadership and work as part of client delivery teams across the service line and the wider SQLI group. The role is primarily billable client work. You will occasionally join client sessions for technical depth, but the consultant carries the relationship. We are looking for someone who can own technical decisions on the build, not only execute, with room to grow toward an AI Architect track as the practice scales.
 
 
 
 
 
 
 How to apply
 
 
 
 
 
 
 Send a short note covering:
 
 
 
 <ol>
 <li>
 
 One thing you have built recently with Claude Code or a Claude-based agent, with a link if possible
 
 
 
 </li>
 </ol>
 <ol>
 <li>
 
 How you would take an agent that touches real client systems from a quick prototype to something safe to run in production
 
 
 
 </li>
 </ol>
 <ol>
 <li>
 
 Your notice period and earliest start date
 
 
 
 </li>
 </ol>
 
 
 Why you&rsquo;ll love working at SQLI?
 
 
 
 
 <ul>
 <li>
 A flexible remote working policy: 3 days per week
 </li>
 <li>
 Continuous learning opportunities and certifications to support your development
 </li>
 <li>
 Personalised support: career follow-up, diverse projects, and strong team collaboration
 </li>
 <li>
 Regular rituals: internal communications on tech and AI topics, internal events, and meet-ups
 </li>
 </ul>
</div>

AI Engineer

Copperleaf Technologies Inc.

<div><div><div><div><h2 class="jobSectionHeader">Company Description</h2></div><div>
IFS is a billion-dollar revenue company with 6000+ employees on all continents. Our leading AI technology is the backbone of our award-winning enterprise software solutions, enabling our customers to be their best when it really matters&ndash;at the Moment of Service&trade;. Our commitment to internal AI adoption has allowed us to stay at the forefront of technological advancements, ensuring our colleagues can unlock their creativity and productivity, and our solutions are always cutting-edge.
At IFS, we&rsquo;re flexible, we&rsquo;re innovative, and we&rsquo;re focused not only on how we can engage with our customers but also on how we can make a real change and have a worldwide impact. We help solve some of society&rsquo;s greatest challenges, fostering a better future through our agility, collaboration, and trust.
We celebrate diversity and understand our responsibility to reflect the diverse world we work in. We are committed to promoting an inclusive workforce that fully represents the many different cultures, backgrounds, and viewpoints of our customers, our partners, and our communities. As a truly international company serving people from around the globe, we realize that our success is tantamount to the respect we have for those different points of view.
By joining our team, you will have the opportunity to be part of a global, diverse environment; you will be joining a winning team with a commitment to sustainability; and a company where we get things done so that you can make a positive impact on the world.
We&rsquo;re looking for innovative and original thinkers to work in an environment where you can #MakeYourMoment so that we can help others make theirs. With the power of our AI-driven solutions, we empower our team to change the status quo and make a real difference.
If you want to change the status quo, we&rsquo;ll help you make your moment. Join Team Purple. Join IFS.</div></div><div><div><h2 class="jobSectionHeader">
Job Description</h2></div><div>
About the Role
As a Forward Deployed AI Engineer, you&rsquo;ll work directly with enterprise customers to deliver custom, production-ready AI solutions that solve real-world problems. You&rsquo;ll lead the design and deployment of intelligent agents across customer workflows&mdash;owning everything from discovery and prototyping to configuration, testing, and launch.
This is a fast-paced, hands-on role that combines engineering, customer collaboration, and applied AI. You will serve as a critical link between our product and the customer&rsquo;s needs&mdash;ensuring rapid value delivery and laying the foundation for long-term success.
What You&rsquo;ll Do<ul><li>
Partner with enterprise customers to scope and implement AI Agent use cases across complex workflows</li><li>
 Integrate IFS Loops platform with customer systems</li><li>
Tune agent behavior and logic to deliver measurable outcomes (e.g., lower costs, increase in efficiency, fewer errors)</li><li>
Troubleshoot deployments and iterate quickly to ensure performance, accuracy, and user adoption</li><li>
Collaborate closely with Product, Engineering, and Customer Success to feed customer insights into the roadmap</li><li>
Document technical decisions and hand off stable deployments to customer engineering or support teams</li></ul></div></div><div><div><h2 class="jobSectionHeader">
Qualifications</h2></div><div>
What We&rsquo;re Looking For<ul><li>
2&ndash;5 years of experience in a software engineering, solutions engineering, or ML deployment role</li><li>
Proficiency in Python and working knowledge of AI/ML frameworks (e.g. OpenAI, Hugging Face, LangChain, Pinecone, Weaviate, etc.)</li><li>
Familiarity with building LLM applications, RAG systems, or conversational AI workflows</li><li>
Experience integrating with enterprise systems via APIs or middleware (e.g. Salesforce, ServiceNow, SAP, Oracle)</li><li>
Ability to translate business problems into technical solutions&mdash;and deliver them fast</li><li>
Strong interpersonal skills; you&rsquo;re just as comfortable on a whiteboard with a customer as you are in code</li><li>
Bias toward action, ownership, and continuous learning in dynamic environments</li></ul>
Nice to Have<ul><li>
Background in SaaS, customer experience, support operations, or manufacturing systems</li><li>
Experience deploying AI in mission-critical environments</li><li>
Prior work with enterprise AI platforms or multi-agent orchestration</li></ul></div></div><div><div><h2 class="jobSectionHeader">
Additional Information</h2></div><div>
What We&rsquo;re Offering<ul><li>
Salary Range: List $150,000 to $170,000 annually + bonus</li><li>
Flexible paid time off, including sick and holiday</li><li>
 Medical, dental, &amp; vision insurance</li><li>
 401K with Company contribution</li><li>
 Flexible spending accounts</li><li>
 Life insurance and disability benefits</li><li>
 Tuition assistance</li><li>
 Community involvement and volunteering events</li></ul> 
M/F/Disabled/Vet VEVRAA Federal Contractor. We are a Drug-Free Workplace. Interested candidates should apply at: www.ifs.com/about/careers-at-ifs
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. VEVRAA Federal Contractor, Equal Opportunity Employer</div></div></div> 

<div><div>
By clicking the link above or any third-party link within this posting, you are leaving this site and going to a third-party website where the third-party website's terms and privacy policy apply</div></div></div>

Forward Deployed AI Engineer: IFS Loops

Bloomberg

<div>
 Location
 
 
 London
 
 
 Business Area
 
 
 Engineering and CTO
 
 
 Ref #
 
 
 10049302
 
 
 
 Description &amp; Requirements
 
 
 
 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.
 
 
 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.
 
 
 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.
 
 
 We are looking for Senior ML Platform Engineers with strong expertise and passion for building platforms for (Gen) AI applications.
 
 
 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.
 
 
 
 Join the AI Group as a Senior ML Platform Engineer and you will have the opportunity to:
 
 
 
 <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
 
 
 </li>
 </ul>
 
 We are looking for a Senior ML Platform Engineer with:
 
 
 
 <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
 
 
 </li>
 </ul>
 We give back to the technology community and you can read more about our outreach at:
 
 
 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.
 
 
 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

Deloitte

<div><div><div><div><h3 class="jobSectionHeader">Basic information
</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">Job description
</h3></div></div><div></div><div><div><div><div>Job Title: AI Data Engineer (Azure)
Location: London Hybrid. Travel to the London office 2 days a week
Duration: 6 months
Contract Start Date: ASAP
Day rate: Competitive (Inside IR35) 
Deloitte
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. 
The Role
We are looking for a highly skilled AI Data Engineer (Contractor) specialising in Azure 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 strong AI/GenAI data pipeline expertise with hands-on Azure, data discovery and analysis. 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. 
Deliverables: Responsibilities but not limited to:
1. Data Engineering &amp; Azure Platform Delivery 
<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>
2. Unstructured Data &amp; NoSQL Engineering<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>
3. Data Discovery, Analysis &amp; Business Engagement<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. Collaboration &amp; Delivery<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> 
Essential Skills and Experience<ul><li><ul><li>
Proven experience as an Azure Data Engineer in end-to-end data platforms</li><li>
Exposure to AI/GenAI data pipelines (e.g. RAG, embeddings, search)</li><li>
Knowledge of Azure AI Search or vector-based retrieval systems</li><li>
Strong hands-on 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 Python and SQL</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> 
Desirable:<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> 
IR35
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;)</div></div></div></div></div></div><div></div>

Contract - AI Data Engineer (Azure)

Accenture

<div><h2 class="jobSectionHeader">Description</h2>
You build the systems that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent system in production, you have owned the eval harness, and you know what happens when your agent fails at 2am because you have lived it.
As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI systems across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements.
This sits at the heart of the AI engineering talent market, demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme.<h2 class="jobSectionHeader">
Key Responsibilities</h2><ul><li>
Design and build production-grade agentic systems end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability</li><li>
Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets</li><li>
Integrate and abstract across multiple LLM providers &mdash; OpenAI, Anthropic, Vertex AI, and open-source models &mdash; with fallback routing, token, cost, and latency management</li><li>
Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring</li><li>
Embed directly with client engineering teams to design, prototype, and deploy agentic solutions &mdash; workshops, proofs of concept, code-with sessions, and architecture walkthroughs</li><li>
Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster</li><li>
Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness; present findings and recommendations to client stakeholders in business terms</li></ul></div>
 
<div><h2 class="jobSectionHeader">Basic Qualifications</h2><ul><li>
5+ years of software engineering experience in production environments</li><li>
Minimum 1 year of hands-on experience designing and deploying agentic AI solutions in a production environment &mdash; non-negotiable</li><li>
Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent &mdash; at production depth, not tutorial level</li><li>
Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs</li><li>
RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering</li><li>
LLMOps fundamentals: eval harness design, prompt versioning, and production observability</li><li>
Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm)</li><li>
Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience</li><li>
Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure</li></ul></div>

AI Native SW Engineering Specialist

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