At a Glance
- Tasks: Design and develop advanced AI solutions that transform legal insights.
- Company: Join a leading tech company revolutionising the legal industry.
- Benefits: Enjoy competitive salary, health perks, and flexible remote work options.
- Why this job: Make a real impact with cutting-edge AI technology in a dynamic environment.
- Qualifications: 2+ years in software engineering with strong Python and AI application experience.
- Other info: Collaborative culture with opportunities for mentorship and career growth.
The predicted salary is between 48000 - 72000 £ per year.
Chambers and Partners is transforming how the world's leading legal professionals access insight and intelligence and we are looking for a Senior AI Engineer to help drive that innovation. In this pivotal role, you will design, develop, and deploy advanced AI and machine learning solutions that power our next generation of products and research capabilities. Collaborating closely with our architecture, research, analytics, and product teams, you will bring creativity and technical expertise to the forefront of our data and technology strategy. This is a hands-on engineering position focused on building and operating production-grade LLM applications on Azure.
Main Duties and Responsibilities:
- Build robust ingestion pipelines for PDFs/Word/Excel/Audio/JSON and semi-structured sources.
- Design RAG systems: chunking strategies, document schemas, metadata, hybrid/dense retrieval, re-ranking, and grounding.
- Manage vector/keyword indexes (e.g., Azure AI Search, pgvector, Pinecone/Weaviate).
- Develop and deploy advanced NLP, information retrieval, and recommendation systems that enhance Chambers and Partners' research and product offerings, including document understanding, automatic summarisation, topic modelling, semantic search, entity recognition, and relationship extraction.
- Design and implement intelligent tagging and metadata enrichment frameworks to categorise and organise legal and market data, improving search, discoverability, and insight accuracy.
- Design, build, and maintain traditional ML and LLM models and pipelines.
- Build LLM apps using LangGraph/LangChain: tools/function calling, structured outputs (JSON Schema), agents, and multi-step reasoning.
- Implement ASR/TTS and multimodal where relevant (e.g., Whisper).
- Choose customisation paths pragmatically: prompt engineering, system prompts, tools, adapters/LoRA, and selective fine-tuning only when needed.
- Fine-tune and optimise ML models and LLMs to enhance performance, efficiency, and relevance for Chambers' research, analytics, and product applications.
- Deploy and operate services on Azure (AKS/ACI/Azure Functions, API Management).
- Implement CI/CD (GitHub Actions/Azure DevOps), Infrastructure as Code (Bicep/Terraform), secrets via Azure Key Vault, private networking.
- Add observability: tracing/telemetry (OpenTelemetry, LangSmith), metrics, logs, cost and token usage monitoring, alerts.
- Ensure reliability: rate-limit handling, retries/backoff, idempotency, circuit breakers, caching (e.g., Redis/semantic cache), fallbacks and degradations.
- Enforce PII handling, data minimisation, redaction, access controls, and auditability.
- Mitigate prompt injection/jailbreak risks; apply content filters/guardrails; track data residency.
- Establish and drive best practices for model versioning, reproducibility, performance monitoring, bias mitigation, data governance, and ethical AI use.
- Document architectural decisions, runbooks, and operational procedures.
- Write clean, tested, maintainable code in Python (and optionally .NET).
- Apply SOLID, TDD/BDD where sensible, code reviews, refactoring, performance profiling.
- Collaborate in an Agile environment; contribute to technical specs and implementation plans.
- Build POCs to de-risk architecture and showcase value; harden POCs into production services.
- Mentor and guide more junior engineers and data scientists; review code; contribute to technical design reviews; raise the collective standard of the team.
- Stay abreast of the AI/ML research landscape and legal-tech/legal-analytics domain to bring relevant innovations into our stack.
Skills and Experience:
- Significant demonstrable experience in software engineering, with 2+ years building LLM/AI applications in production.
- Strong in Python, API design, asynchronous programming, and integration patterns.
- Proven ability to scale LLMs and other AI models for high-volume, real-world applications, including optimising inference, managing computational resources, and ensuring reliability and maintainability.
- Strong expertise in Python and relevant ML/LLM libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
- Hands-on with LangGraph/LangChain, LlamaIndex or Semantic Kernel for orchestration (tools, agents, guards, structured I/O).
- Familiarity with Azure OpenAI and at least one open model stack (e.g., Llama/Mistral via vLLM/TGI/Ollama).
- Proficient with front-end frameworks such as Angular for integration of AI-powered applications.
- Experience with graph databases and knowledge graphs (Neo4j) for knowledge graphs and tool routing.
- Production deployments on Azure (AKS/ACI/Functions), CI/CD, and Infrastructure as Code (Bicep/Terraform).
- Experience with relational/semi-structured database (MS SQL and Cosmos DB) and vector search indexing (Azure AI Search/pgvector/Pinecone/Weaviate/Milvus/Qdrant) plus Neo4j or equivalent graph database.
- Able to implement key architectural outcomes, including reusability, performance, separation of concerns, and quality integrity.
- Experience in asynchronous programming, API design, and integration patterns.
- Strong understanding of security, compliance, and ethical AI practices, including Key Vault, private endpoints, PII handling, RBAC, data governance, and bias mitigation.
Person Specification:
- A passionate software engineer/Data Scientist with a history of driving their own technical and professional development.
- Worked in the media, publishing, research or a similar consumer-focused industry (Highly Desirable).
- Able to clearly communicate complex technical subjects to team members and stakeholders.
- Able to lead, providing thought leadership in their domain.
- Focused on the finer details that make the difference.
- Pragmatic and driven to get solutions live.
- A proactive attitude. A self-starter who seeks out opportunities for themselves and their team.
- Aware of industry trends – such as challenges and best practices.
- Positive attitude – generating enthusiasm among team members.
- Able to build strong personal relationships and trust.
Equal Opportunity Statement:
We are committed to fostering and promoting an inclusive professional environment for all of our employees, and we are proud to be an equal opportunity employer. Diversity and inclusion are integral values of Chambers and Partners and are key in our culture. We are committed to providing equal employment opportunities for all qualified individuals regardless of age, disability, race, sex, sexual orientation, gender reassignment, religion or belief, marital status, or pregnancy and maternity.
Senior AI/Machine Learning Engineer in London employer: Chambers & Partners
Contact Detail:
Chambers & Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI/Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI and machine learning projects. Whether it's GitHub repos or a personal website, let your work speak for itself. This is your chance to shine!
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and real-world problem-solving scenarios. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at Chambers and Partners.
We think you need these skills to ace Senior AI/Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior AI/Machine Learning Engineer role. Highlight relevant experience and skills that match the job description, especially your work with LLMs and AI applications.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're the perfect fit for this position. Share your passion for AI and machine learning, and how your background aligns with our mission at Chambers and Partners.
Showcase Your Projects: Include specific examples of projects you've worked on that demonstrate your expertise in AI and machine learning. We love seeing real-world applications of your skills, so don't hold back!
Apply Through Our Website: For the best chance of success, apply directly through our website. It streamlines the process and ensures your application gets to the right people quickly!
How to prepare for a job interview at Chambers & Partners
✨Know Your Tech Inside Out
Make sure you’re well-versed in the specific technologies mentioned in the job description, like Python, Azure, and LLM frameworks. Brush up on your knowledge of AI/ML concepts and be ready to discuss how you've applied them in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to discuss past projects where you tackled complex problems, especially those related to AI and machine learning. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your contributions.
✨Understand the Company’s Vision
Research Chambers and Partners and their approach to legal tech. Be ready to explain how your skills can help drive their innovation forward, particularly in areas like retrieval-augmented generation and intelligent tagging.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the role and the company. Inquire about their current projects, team dynamics, or future goals in AI. This not only demonstrates your enthusiasm but also helps you gauge if the company is the right fit for you.