Senior AI Solutions Engineer

As a Senior AI Solutions Engineer, you'll design, build, and run AI solutions that make a real difference in day-to-day decision-making across the business. This is a hands-on engineering role focused on shipping AI into production, not prototypes.

You'll work across Python + Java microservices, LLM/RAG systems, vector search, and data pipelines, deploying to AWS (incl. Bedrock) and Azure (Azure AI Foundry). You'll partner closely with the Lead AI Solutions Engineer, platform engineers, analysts, and data teams to deliver scalable capabilities that are secure, observable, and maintainable.

What you'll do Build production AI systems (LLMs + RAG)

Design and implement RAG-powered services (assistants, chat experiences, semantic search) using modern LLM patterns

Improve retrieval quality through embeddings, metadata enrichment, ranking strategies, and evaluation feedback loops

Build modular components that can be reused across multiple use cases and domains

Develop scalable APIs and microservices

Build and maintain backend services and APIs using Python (FastAPI/LangChain/Hugging Face) and Java

Create clean service boundaries, versioned APIs, and secure integration patterns for enterprise environments

Produce high-quality documentation and maintain an engineering standard that scales beyond one team

Engineer reliable data and embedding pipelines

Build and operate pipelines for ingestion, embedding generation, chunking strategies, and metadata processing

Orchestrate ETL/ELT workflows using Airflow for batch and near-real-time use cases

Ensure governance, security, and privacy requirements are met (and provable)

Operate in cloud with strong engineering hygiene

Deploy solutions across AWS and Azure, using CI/CD and IaC to keep releases safe and repeatable

Containerise and run workloads with Docker and Kubernetes, working with Platform Engineering on Kindred Cloud

Build with production realities in mind: logging, monitoring, failure handling, scalability, and cost controls

Own semantic search and vector database performance

Implement and optimise vector search using PGVector / ChromaDB, including indexing strategies and query performance

Work with Sentence Transformers / OpenAI embeddings and similarity techniques (e.g., cosine similarity) to improve precision/recall

Collaborate, influence, and raise the bar

Work across teams to align on design choices, integration patterns, and shared reusable components

Mentor others through reviews, pairing, and knowledge-sharing sessions

Bring pragmatic innovation: test new approaches, keep what works, and productise it

What success looks like

AI features move from idea production with measurable adoption and value

RAG systems deliver relevant, trustworthy outputs with clear performance indicators

Services are secure, observable, and operationally stable (not fragile demos)

Engineers and stakeholders trust the platform and can build on it without reinventing the wheel

Do you have experience in Terraform?, Do you have a Master's degree?, 5+ years in backend engineering, data engineering, or AI/ML integration roles

Strong hands-on skills in Python and solid experience with Java (or deep JVM ecosystem experience)

Practical experience building with LLMs, embeddings, semantic search, and RAG-style architectures

Experience with vector databases (PGVector/ChromaDB or similar) and retrieval optimisation

Strong delivery habits: CI/CD, Docker, Kubernetes, and Infrastructure as Code (Terraform/CloudFormation)

Cloud experience across AWS (EC2, S3, Lambda, Bedrock, CodePipeline etc.) and/or Azure AI Foundry

Comfortable working with stakeholders, ambiguity, and trade-offs - you can turn fuzzy problems into shipped outcomes

Nice to have

Experience fine-tuning or adapting models for domain use cases

Experience building internal developer platforms or reusable AI components

Experience with evaluation/observability for GenAI systems (quality, latency, cost, drift, safety)

Prior experience in regulated environments or with identity/security integrations (SSO, IAM)

Well-being allowance Learning and development opportunities Inclusion networks Charity days Long service awards Social events and activites Private medical insurance Life assurance and income protection Employee Assistance Programme Pension Meet the recruiter Maxim Martea

At FDJ UNITED, we don't just follow the game, we reinvent it. FDJ UNITED is one of Europe's leading betting and gaming operators, with a vast portfolio of iconic brands and a reputation for technological excellence. With more than 5,000 employees and a presence in around fifteen regulated markets, the Group offers a diversified, responsible range of games, both under exclusive rights and open to competition. We set new standards, proving that entertainment and safety can go hand in hand. Here, you'll work alongside a team of passionate individuals dedicated to delivering the best and safest entertaining experiences for our customers every day. We're looking for bold people who are eager to succeed and ready to level-up the game. If you thrive on innovation, embrace challenges, and want to make a real impact at all levels, FDJ UNITED is your playing field. Join us in shaping the future of gaming. Are you ready to LEVEL-UP THE GAME?, Modern stack: LLMs, RAG, vector search, Kubernetes, multi-cloud Strong cross-functional collaboration with data, platform, and product teams Space to innovate, improve foundations, and build capabilities that scale Our Way Of Working Our world is hybrid. A career is not a sprint. It's a marathon. One of the perks of joining us is that we value you as a person first. Our hybrid world allows you to focus on your goals and responsibilities and lets you self-organise to improve your deliveries and get the work done in your own way. Application Process We believe talent knows no boundaries. Our hiring process focuses solely on your skills, experience, and potential to contribute to our team. We welcome applicants from all backgrounds and evaluate each candidate based on merit, regardless of personal characteristics as the age, gender, origin, religion, sexual orientation, neurodiversity or disability.