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 technology.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Diverse and inclusive workplace committed to your career development.
- Why this job: Make a real impact on legal processes with cutting-edge AI solutions.
- Qualifications: Experience in Azure Databricks and machine learning; 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 access to cutting-edge technology and the opportunity to work alongside talented professionals in a dynamic environment that prioritises employee growth and development. With a commitment to diversity and a focus on creating a sense of belonging, DLA Piper offers a rewarding career path that empowers you to make a meaningful impact in the legal sector through advanced AI solutions.
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 ML models. 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 a collaborative environment.
✨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 Application:Make sure to customise your CV and cover letter to highlight your experience with Azure Databricks, MLflow, and LLMs. We want to see how your skills align with the role, so don’t hold back on showcasing relevant projects!
Showcase Your Collaboration Skills:Since this role involves working closely with various teams, it’s a good idea to mention any past experiences where you collaborated with engineers, data scientists, or business stakeholders. We love seeing teamwork in action!
Highlight Your Problem-Solving Abilities:We’re looking for someone who can troubleshoot and improve AI workflows. Share examples of challenges you’ve faced in previous roles and how you tackled them. This will show us your analytical thinking and adaptability.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
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 ability to troubleshoot and optimise AI workflows. Prepare to discuss how you've monitored and improved models in production, and be ready to provide specific examples of challenges you've overcome in your previous roles.
✨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. Mention any recent developments in LLMOps or agentic AI that you've explored, and how you plan to apply them in your work.
