AI Senior Engineer

Our client is transforming how fund formation and private equity legal work gets done. Their flagship product is a legal tech SaaS platform that streamlines fund documentation and workflows for law firms and institutional fund managers. They are an early-stage company with clear product–market fit, a deep understanding of their buyers, significant market traction and an ambitious roadmap. They are now looking for a Senior AI Engineer to help define the future of AI in the platform. This is a rare opportunity to join a lean, high-calibre team where the bar is high, the work is hands-on, and your impact on the company's growth will be direct and visible. The team moves fast, takes ownership, stays close to its customers, and values clear thinking and simplicity over complexity. Role Overview You will join the product engineering team and lead the development of AI-powered features within the platform. This is a hands-on applied research and engineering role focused on natural language processing, machine learning, and the deployment of large language models (LLMs) into production SaaS environments at scale. You will design and build models that enhance legal document understanding, search, summarisation and workflow automation, while ensuring solutions are performant, reliable, secure and maintainable in a production-grade cloud environment. From data pipelines and model evaluation to inference optimisation and guardrails, you will own key parts of the AI stack and help establish best practices for shipping AI features in enterprise SaaS. What You Will Be Doing

• Design and implement ML models to improve document parsing, search, classification, and summarisation.
• Integrate large language models (LLMs) into core product workflows, with emphasis on reliability, performance, and guardrails against errors.
• Collaborate with engineers, product managers, QA and customer-facing teams to deliver AI-driven features aligned with client needs.
• Optimise model serving and inference pipelines for low latency and cost efficiency in AWS (ECS, Lambda, S3, CloudWatch).
• Develop data pipelines for training and evaluation, leveraging existing stores (PostgreSQL, Redis, Elasticsearch/OpenSearch, S3).
• Ensure models meet scalability, security, and compliance requirements for enterprise SaaS deployments.
• Stay current on advancements in NLP, LLMs, and applied ML; bring innovations into production when appropriate.
• Contribute to documentation, code reviews, and knowledge sharing across the engineering organisation.

Must-Have Requirements

• 5+ years of proven experience as an AI/ML Engineer or similar role, delivering NLP and ML models into production SaaS platforms.
• Strong knowledge of machine learning fundamentals and hands-on experience with NLP libraries/frameworks (e.g. spaCy, Hugging Face Transformers, PyTorch, TensorFlow).
• Demonstrated experience deploying and scaling large language model applications in production (e.g. fine-tuning, retrieval-augmented generation, evaluation, monitoring).
• Solid programming skills in Python (preferred) with experience in building APIs and integrating AI models into applications.
• Understanding of distributed systems and cloud environments (AWS preferred: ECS, Lambda, S3, CloudWatch).
• Experience with data pipelines and orchestration for model training, evaluation, and monitoring.
• Ability to evaluate trade-offs between accuracy, cost, performance, and interpretability in applied AI systems.
• English at a level (B2+) sufficient for daily communication with the team.

Preferred Requirements

• Experience with legal technology or document-heavy domains.
• Familiarity with vector databases and semantic search (e.g. Elasticsearch, OpenSearch, Pinecone, FAISS).
• Knowledge of prompt engineering, fine-tuning, and evaluation techniques for LLMs.
• Experience integrating AI safety, compliance, and explainability into deployed solutions.
• Exposure to front-end frameworks (React, TypeScript) and how AI integrates into end-user experiences.

Personal Attributes

• Passionate about applying AI to real-world, high-value problems.
• Strong problem-solver with a pragmatic mindset: balances cutting-edge techniques with production readiness.
• Excellent communicator, able to collaborate across technical and non-technical teams.
• Curious, self-motivated, and committed to continuous learning and improvement.

How They Work Teams work in Agile Scrum squads, supported by strong CI/CD, IaC (Terraform/Terragrunt), and security-first practices (SOPS, KMS). All requirements live in Confluence and all work items live in Jira. If you are excited by the opportunity to bring modern NLP and LLM capabilities into a production platform used by demanding professional users, apply now.