Job Purpose
RWS is a global leader in content, translation, and intellectual property services. With more than 60 years of experience, RWS helps the world's top brands grow by ensuring they are understood anywhere, in any language. The company combines proprietary technology with deep human expertise to deliver high-quality, compliant, and scalable solutions across industries such as life sciences, technology, finance, and legal.
Training or fine-tuning artificial intelligence (AI) requires data. LOTS of data. However, not just any data will do – our clients need responsible AI data that's targeted, accurate and reliable to ensure machine learning (ML) success. But preparing AI training data is a monumental task that can take up the vast majority of AI project time, leaving AI teams with precious little time to focus on developing, deploying and evaluating ML models.
TrainAI by RWS helps our clients address this challenge head-on. With a seamless blend of technological understanding and human intelligence, TrainAI provides complete, end-to-end data collection and content generation, data annotation or labelling, human-in-the-loop data validation and generative AI data services for all types of AI, in any language, at any scale, based on the principles of responsible AI. Today, TrainAI supports four of the world's top five technology companies, enhancing the performance of their generative AI by providing services such as prompt engineering, response refinement and red teaming with locale-specific domain experts across a broad range of topic areas and educational levels.
We're looking for a mid-level product focused engineer to join our team. You'll own features and small products end-to-end—design, build, ship, iterate—using AI tools as your primary means of execution. You'll be working with AI agents but bringing your own product judgment to every decision. We move fast because AI multiplies what one engineer can do, and this role is built for that.
Responsibilities
•Own features across the full lifecycle: scope the problem, prototype, ship to production, and iterate on feedback
•Use AI coding agents as your default workflow - delegating implementation, reviewing and directing output, and going from idea to working software quickly
•Turn product goals into technical decisions without waiting for a fully detailed spec
•Work across the stack (backend, frontend, and often design/UX) as the problem requires
•Collaborate with senior engineers and product to sharpen your product and technical instincts
Requirements
•2–4 years of software engineering experience with solid fundamentals - you can read, evaluate, and debug code you didn't write line-by-line
•Hands-on experience with AI development tools, or strong evidence you'll pick them up fast
•Emerging product sense: you care about the user problem and can form opinions about what to build
•Comfort with ambiguity and ownership—you'd rather ship and learn than wait for perfect requirements
•Ability to work across at least a couple of areas of the stack
•Bias toward action and rapid iteration
•Experience on a small team or shipping something you scoped yourself
•Familiarity with prompt engineering, evals, or AI-powered features
•Some design or product exposure beyond pure engineering
Why Is This Role Different?
You're not inheriting a backlog, you're owning a product area with real scope and real stakes. The engineering team you'll work with ships fast using agentic tooling as their default; you're expected to match that pace in how you work too, not just in what you ask for.
Life at RWS
If you like the idea of working with smart people who are passionate about growing the value of ideas, data and content by making sure organizations are understood, then you'll love life at RWS. Our purpose is to unlock global understanding. This means our work fundamentally recognizes the value of every language and culture. So, we celebrate difference, we are inclusive and believe that diversity makes us strong. We want every employee to grow as an individual and excel in their career.
