How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Role Overview
The AI Engineer will be responsible for designing, deploying, managing, and optimising AI products, machine learning models, and agentic AI workflows. Leveraging the Azure ecosystem, the role will focus on delivering production-ready AI/ML infrastructure and applications that are scalable, secure, governed, and cost-effective.
The AI Engineer will support the development of Data & AI products that accelerate DLA’s ambition to enhance legal processes through innovative technologies, improve operational efficiency, and deliver data-driven insights for better decision-making. This role will work closely with platform engineers, data scientists, data engineers, and business stakeholders to move AI solutions from experimentation into reliable production use.
Main Duties and Responsibilities
- Design, develop, deploy, and optimise machine learning models and LLM-based solutions using Azure Databricks, Azure ML, or Azure AI Foundry
- Build and maintain scalable LLM-powered applications, ensuring performance, reliability, and cost efficiency in production
- Develop and support agentic AI workflows for autonomous or semi-autonomous task execution and orchestration
- Build and maintain pipelines that support AI/ML workflows, including data preparation, experimentation, evaluation, deployment, and monitoring
- Collaborate with platform engineers, data scientists, data engineers, and business stakeholders to integrate AI/ML solutions into production environments
- Implement and optimise retrieval, prompting, tool-calling, and orchestration patterns for enterprise AI applications
- Develop AI services and workflows using LangChain, LangGraph, or similar frameworks for multi-step reasoning and orchestration
- Enable standardised tool and context integration across AI applications using MCP or similar interoperability patterns
- Monitor, troubleshoot, and continuously improve models and AI workflows in production to ensure reliability, quality, and accuracy
- Apply LLMOps and MLOps best practices across experimentation, versioning, deployment, monitoring, and lifecycle management
- Ensure AI/ML solutions align with cloud governance, security, compliance, and responsible AI requirements
- Document models, workflows, engineering patterns, and deployment processes to support reproducibility and knowledge sharing
- Stay current with emerging AI/ML, LLMOps, and agentic AI capabilities and apply them pragmatically to improve existing solutions
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
About You
- Hands-on experience with Azure Databricks, Azure ML, and ideally Azure AI Foundry
- Strong experience deploying and managing LLMs and machine learning models in enterprise cloud environments
- Experience using MLflow for experiment tracking, model lifecycle management, and versioning of both traditional ML models and LLM-based solutions
- Strong understanding of LLMOps practices, including deployment, monitoring, scaling, evaluation, governance, and cost control
- Experience building agentic AI workflows and orchestration patterns using frameworks such as LangChain, LangGraph, or similar
- Understanding of Model Context Protocol (MCP) or equivalent approaches for standardised integration between AI applications, tools, and enterprise data sources
- Strong Python engineering skills, including experience with libraries and frameworks such as PyTorch, Pydantic, LangChain, and LangSmith
- Experience with prompt orchestration, structured outputs, evaluation, and tool-calling patterns for LLM applications
- Knowledge of RAG patterns, vector search, and enterprise retrieval approaches
- Understanding of cloud governance, compliance, and responsible AI controls
- Good understanding of key Azure services such as Virtual Machines, Active Directory, Automation, and related cloud infrastructure
- Experience building and supporting ETL and workflow pipelines using Azure Data Factory, Databricks workflows, or similar
- Experience with containerisation and orchestration tools such as Docker and Kubernetes
- Experience with version control systems, particularly GitLab, and CI/CD pipelines
- Familiarity with Agile product development environments, including sprint planning, stand-ups, and retrospectives
- Strong understanding of data structures, transformation logic, and integration patterns
- Ability to communicate effectively with technical and non-technical stakeholders
- Collegiate, pragmatic, and delivery-focused, with a willingness to support broader team goals
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, AI / ML Engineering, or a related field
- 5+ years of experience in machine learning and data engineering
- Proven experience with Azure Databricks and other Azure services (e.g., Azure ML, AI Foundry)
About Us
We're a global law firm helping our clients achieve their goals wherever they do business. Our pursuit of innovation has transformed our delivery of legal services. With offices in the Americas, Europe, the Middle East, Africa and Asia Pacific, we deliver exceptional outcomes on cross-border projects, critical transactions and high-stakes disputes.
For our people, that means a world of opportunity. You'll shape the future, have the freedom to seize opportunities, and discover your own path. Together, we unlock our potential and redefine what we can achieve.
At DLA Piper, diversity, equity, and inclusion is about creating a sense of belonging. We strive towards a workplace and culture where everyone feels that they belong, that their voice counts and that they can prosper in their career. For us, diversity is about the unique blend of talents, skills, experiences, and perspectives that make each of us an individual. We are committed to being accessible and accommodating any reasonable adjustments needed throughout the recruitment process to ensure an inclusive experience for all. If you need any support or adjustments, please let us know.
We recognise that people have responsibilities and interests outside of their career and that as a business, we all benefit from working flexibly. That's why we are open to agile working.
Where local legislation permits, we will conduct relevant pre-engagement screening checks prior to your first day.
Apply now
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location