Location: Remote Reporting To: CTO Department: Engineering & Architecture
About Intelligent Legal Solutions (ILS)
At Intelligent Legal Solutions (ILS), we’re transforming how fund formation and private equity legal work gets done. Our flagship product, ProVision, is a legal tech SaaS platform that streamlines fund documentation and workflows for law firms and institutional fund managers. We’re still early, but we have a clear product—market fit, a deep understanding of our buyers, and an ambitious roadmap. We operate at the intersection of legal, private equity, and workflow automation, and we’re building the go-to platform for fund formation teams globally. This is a rare opportunity to join a lean, high-calibre team that is seeing significant traction in the marketplace. The bar is high, the work is hands-on, and the impact on the company’s growth, brand, and revenue will be direct and visible. We move fast, take ownership, and stay close to our customers. We value clear thinking, simplicity over complexity. If you want to do the best work of your career in legal tech, we’d love to build with you.
Role Overview
We are seeking a Senior AI Engineer to join our product engineering team and lead the development of AI-powered features within ProVision. 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. The successful candidate will design and build models that enhance legal document understanding and workflow automation, while ensuring solutions are performant, reliable, and maintainable in a production-grade cloud environment.
What You Will Be Doing
Design and implement ML models to improve document parsing, search, classification, and summarization.
Integrate large language models (LLMs) into core product workflows, with emphasis on reliability, performance, and guardrails against errors.
Collaborate with engineers, product managers, and QA to deliver AI-driven features aligned with client needs.
Optimize 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 organization.
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, complian
