AI Engineer @ RemoDevs

Experience as an AI/ML Engineer or similar, delivering NLP and ML models in SaaS. Strong ML knowledge with hands-on use of NLP libraries (spaCy, Hugging Face, PyTorch, TensorFlow). Experience deploying and scaling LLM apps (fine-tuning, RAG, evaluation, monitoring). Strong Python skills (preferred) and experience building APIs and connecting AI models to apps. Knowledge of distributed systems and cloud (AWS preferred: ECS, Lambda, S3, CloudWatch). Experience with data pipelines for training, testing, and monitoring models. Ability to balance accuracy, cost, speed, and explainability in applied AI systems. About Us We build B2B legal technology that helps law firms and fund managers work faster and with higher quality. Our main product, our platform, makes legal work for raising private investment funds easier. It helps lawyers speed up drafting, negotiation, and compliance at scale. We run a single-tenant SaaS system on AWS in different regions. Our tech stack includes Python/Django 4.2, React 18/TypeScript, PostgreSQL, Redis, Elasticsearch/OpenSearch, S3, ECS, and Lambda. Our teams work in Agile Scrum with strong CI/CD, IaC (Terraform/Terragrunt), and security-first practices (SOPS, KMS). Role Overview We are looking for a Mid–Senior AI Engineer to join our product team and lead AI features in our platform. This is a hands-on role focused on natural language processing (NLP), machine learning (ML), and large language models (LLMs) in production SaaS at scale. You will design and build models to improve legal document understanding and automate workflows. The solutions must be fast, reliable, and safe for production use in the cloud. Key Responsibilities Research, design, and build NLP and ML models for document parsing, search, classification, and summarization. Add LLMs into main product workflows, making sure they are reliable, performant, and safe. Work with engineers, product managers, and QA to deliver AI features that meet client needs. Improve model serving and inference for low latency and cost in AWS (ECS, Lambda, S3, CloudWatch). Build data pipelines for training and testing using PostgreSQL, Redis, Elasticsearch/OpenSearch, and S3. Ensure models meet security, compliance, and scale needs for enterprise SaaS. Stay up to date with new NLP, LLM, and ML research and bring useful ideas to production. Contribute to documentation, code reviews, and knowledge sharing in the engineering team. Essential Requirements Experience as an AI/ML Engineer or similar, delivering NLP and ML models in SaaS. Strong ML knowledge with hands-on use of NLP libraries (spaCy, Hugging Face, PyTorch, TensorFlow). Experience deploying and scaling LLM apps (fine-tuning, RAG, evaluation, monitoring). Strong Python skills (preferred) and experience building APIs and connecting AI models to apps. Knowledge of distributed systems and cloud (AWS preferred: ECS, Lambda, S3, CloudWatch). Experience with data pipelines for training, testing, and monitoring models. Ability to balance accuracy, cost, speed, and explainability in applied AI systems. Preferred Requirements Experience in legal tech or document-heavy industries. Familiarity with vector databases and semantic search (Elasticsearch, OpenSearch, Pinecone, FAISS). Knowledge of prompt engineering, fine-tuning, and testing LLMs. Experience with AI safety, compliance, and explainability. Understanding of front-end frameworks (React, TypeScript) and AI integration in user-facing apps. Personal Attributes Passion for solving real-world problems with AI. Practical problem-solver who balances new methods with production needs. Good communicator with both technical and non-technical teams. Curious, self-driven, and always learning. What We Offer Competitive pay package. Growth opportunities in a fast-moving tech company. Remote-first culture with international teammates. Work with modern legal-tech and global clients. This senior role is a chance to shape the future of our platform — working across the stack to deliver innovative features for leading law firms worldwide. ,[Research, design, and build NLP and ML models for document parsing, search, classification, and summarization., Add LLMs into main product workflows, making sure they are reliable, performant, and safe., Work with engineers, product managers, and QA to deliver AI features that meet client needs., Improve model serving and inference for low latency and cost in AWS (ECS, Lambda, S3, CloudWatch)., Build data pipelines for training and testing using PostgreSQL, Redis, Elasticsearch/OpenSearch, and S3., Ensure models meet security, compliance, and scale needs for enterprise SaaS., Stay up to date with new NLP, LLM, and ML research and bring useful ideas to production., Contribute to documentation, code reviews, and knowledge sharing in the engineering team.] Requirements: Python, Machine learning, NLP