At a Glance
- Tasks: Design and optimise AI products and machine learning models using Azure technologies.
- Company: Join DLA Piper, a leader in legal innovation and diversity.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on diversity and inclusion.
- Why this job: Make a real impact on legal processes with cutting-edge AI technology.
- Qualifications: Experience in AI/ML, Azure services, and strong Python skills required.
The predicted salary is between 60000 - 80000 £ per year.
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.
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.
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.
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
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.
AI/ML Engineer employer: DLA Piper
DLA Piper is an exceptional employer that fosters a collaborative and inclusive work culture, where innovation thrives and every voice is valued. As an AI/ML Engineer, you will have the opportunity to work with cutting-edge technologies in a supportive environment that prioritises professional growth and development, ensuring you can advance your career while contributing to meaningful projects that enhance legal processes. Located in a vibrant area, DLA Piper offers a dynamic workplace that encourages creativity and teamwork, making it an ideal place for those looking to make a significant impact in the field of AI and machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land AI/ML Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the AI/ML space on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those using Azure Databricks or MLflow. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common AI/ML questions and practical scenarios. Practice explaining your past projects and how you tackled challenges, especially in deploying and managing LLMs.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AI/ML Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI/ML Engineer role. Highlight your experience with Azure Databricks, MLflow, and any relevant projects that showcase your skills in deploying and managing machine learning models.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background aligns with our mission at DLA Piper. Don’t forget to mention specific technologies you’ve worked with, like LangChain or Azure ML.
Showcase Your Projects:If you've got any personal or professional projects related to AI/ML, make sure to include them. We love seeing practical applications of your skills, especially if they involve agentic AI workflows or LLM-based solutions!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status directly!
How to prepare for a job interview at DLA Piper
✨Know Your Tech Stack
Make sure you’re well-versed in Azure Databricks, Azure ML, and any other relevant tools mentioned in the job description. Brush up on your experience with LLMs and machine learning models, as you'll likely be asked to discuss specific projects or challenges you've faced.
✨Showcase Collaboration Skills
This role involves working closely with various teams, so be prepared to share examples of how you've successfully collaborated with platform engineers, data scientists, and business stakeholders in the past. Highlight your communication skills and how you bridge the gap between technical and non-technical team members.
✨Demonstrate Problem-Solving Abilities
Expect questions that assess your problem-solving skills, especially in relation to AI workflows and model optimisation. Prepare to discuss how you've tackled issues in production environments and what strategies you used to ensure reliability and performance.
✨Stay Current with Trends
The field of AI/ML is constantly evolving, so show your enthusiasm for staying updated on emerging technologies and best practices. Be ready to discuss recent advancements in LLMOps or agentic AI that you find exciting and how they could apply to the role.
