Mid/Senior AI Engineer / Data Scientist (Full-Stack & Systems)

Company: FactTrace Location: Cambridge, UK (Hybrid: Office-based with flexibility) Job Type: Full-time About FactTrace FactTrace comes from two roots: Fact (verified truth) and Trace (the ability to follow and verify). Together, they express a simple, vital idea: truth that can be followed, even as its form changes. We are building the truth infrastructure for the AI era , a foundation that preserves the integrity of meaning as language moves between people, systems, and machines. As enterprise, institutional, and governmental decision-making relies increasingly on fast-moving, AI-generated text, the ability to verify what has remained true through change is essential. By 2030, deterministic verification of textual information will not just be an advantage, it will be a requirement. FactTrace exists to build that layer. Located in the heart of Cambridge's tech ecosystem, we offer a dynamic culture where operational excellence, supportive collaboration, and technical rigor drive everything we do. The Mindset Building infrastructure for the AI era requires generalists with a deep engineering toolkit and a commitment to the company's success. We aren't looking for someone who only wants to tweak model parameters in isolation. We need an adaptable problem solver who takes true ownership. One day you might be evaluating embedding models or optimizing a vector retrieval architecture; the next, you could be configuring AWS SQS queues, fixing a Docker deployment, writing custom parsers for complex PDFs/XMLs, or jumping into React to connect a backend service to the user interface. If you thrive on high agency, variety, and a "whatever it takes to ship" attitude, you’ll fit right in. What You’ll Be Doing * Truth \& Verification Systems: Design, build, and evaluate production-grade LLM workflows , Vector Retrieval systems , and custom embedding pipelines to power deterministic text verification. * Complex Data Parsing: Extract, parse, and structure messy, real-world document formats ( PDF, XML ) to preserve source integrity. * Backend \& Event-Driven Architecture: Write clean, scalable Python microservices, optimize SQL databases, and manage asynchronous data flows via AWS SQS queues . * Vector Search \& Infrastructure: Deploy and manage high-dimensional vector search with Milvus , containerize services using Docker , and oversee cloud infrastructure on AWS . * Observability \& Full-Stack Flow: Implement end-to-end telemetry for model health and system performance, while collaborating on frontend integrations in React . - What We’re Looking For 1. The Right Attitude (Most Important) * Grit \& Ownership: A high-agency approach to problem-solving and a deep personal commitment to FactTrace’s mission and commercial success. * Context Switching: Comfort moving fluidly between AI research, backend engineering, cloud DevOps, and lightweight UI tweaks. * Cambridge Presence: A collaborative team player who values regular face-to-face time in our Cambridge office to build momentum alongside the team. - 2. Technical Toolkit * AI \& NLP: Experience with LLM development/research , advanced RAG architectures , embeddings , and vector databases ( Milvus ). * Software Engineering: Strong Python , SQL , document parsing ( PDF, XML ), and asynchronous messaging ( SQS ). * DevOps \& Cloud: Hands-on experience with Docker , core AWS services, microservices architecture, and system telemetry/logging . * Frontend: Working knowledge of React (or a willingness to touch the UI when needed). Why Join FactTrace? * Mission-Critical Impact: Work on the defining challenge of the AI era—ensuring trust, traceability, and truth in automated information. * Career Acceleration: High-visibility, cross-functional role in a supportive environment with ample room for professional growth. * Cambridge Tech Hub: Enjoy our vibrant office culture with hybrid flexibility, right in the center of world-class innovation. - Ready to Help Build Truth Infrastructure? If you have the right mindset, love solving full-stack engineering challenges, and want to help shape the future of AI Trust, we want to hear from you. Apply directly on LinkedIn