3 days ago
London, United KingdomSenior
Responsibilities
- Design, develop, and deploy Generative AI solutions using LLMs, RAG architectures, and vector databases.
- Build AI applications for document intelligence, compliance automation, and conversational banking.
- Develop scalable data pipelines and lakehouse architectures using Databricks, Spark, Snowflake, and cloud-native services.
- Integrate structured and unstructured data for analytics and AI use cases.
- Deploy, monitor, and manage AI/ML solutions on Azure, AWS, or GCP.
- Implement CI/CD, model governance, monitoring, and lifecycle management for AI systems.
- Build APIs, microservices, and cloud-native platforms supporting enterprise AI applications.
- Establish data governance, lineage, quality, explainability, bias mitigation, and auditability frameworks.
- Collaborate with stakeholders across risk, compliance, trading, fraud detection, and portfolio analytics.
- Drive architecture decisions, mentor engineering teams, and evaluate emerging AI technologies.
Requirements
- At least 7 years of experience in Data Engineering, AI Engineering, or Machine Learning platforms.
- Strong expertise in Python, SQL, Generative AI frameworks, cloud platforms, and distributed data processing.
- Hands-on experience with Spark/PySpark, Databricks, cloud-native data platforms, APIs, microservices, and cloud-based AI applications.
- Strong understanding of Generative AI, LLMs, RAG architectures, embeddings, vector databases, MLOps, CI/CD, model monitoring, governance, and Responsible AI.
- Proven experience delivering AI or data solutions in banking, capital markets, insurance, fintech, or other regulated financial environments.
- Understanding of financial-services processes, regulatory requirements, data privacy, and governance frameworks including GDPR, AML, and KYC.
- Experience leading teams, mentoring engineers, driving technical initiatives, and establishing engineering best practices.
- Ability to translate business requirements into scalable data and AI solutions and communicate effectively with business and technology stakeholders.
- Experience working in Agile/Scrum delivery environments.
Benefits
- Hybrid working across company offices, client sites, and home, with no option to work from home 100% of the time.
- Wellbeing support including Mental Health Champions and access to Thrive and Peppy wellbeing apps.
- Training and development opportunities including thinktanks, hackathons, up to 250,000 courses, and external certifications.
- Inclusive recruitment practices through Capgemini's Disability Confident Employer Level 2 commitment.
Tech Stack
Categories
AI ApplicationsData Engineering
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.