ai engineer for financial services

HireHi; Greater London; On-site; GBP 90,000 - 140,000; Full time

Benefits offered by this job

Wellbeing support

Professional development

Job summary

Capgemini is a global AI-powered technology partner delivering value through AI and engineering services. The role focuses on designing, building, and deploying end-to-end Generative AI solutions across banking, risk, compliance, and portfolio analytics.

You will lead initiatives across data pipelines, governance, and MLOps while collaborating with stakeholders to meet regulatory and security standards.

Qualifications

• 7+ years in Data/AI Engineering or ML platforms.
• Strong Python/SQL and GenAI framework experience.
• Experience with cloud platforms and distributed data processing.

Responsibilities

• Design, develop, and deploy end-to-end Generative AI solutions using LLMs, RAG, and vector databases.
• Build AI-driven apps for document intelligence, compliance automation, and conversational banking.
• Develop scalable data pipelines and lakehouse architectures (Databricks, Spark, Snowflake).
• Integrate data sources to support analytics and AI use cases.
• Deploy, monitor, and manage AI/ML solutions on Azure, AWS, or GCP with MLOps.

Skills

Python

SQL

GenAI frameworks

Cloud platforms

Distributed data processing

LLMs/RAG architectures

MLOps

Team leadership

Problem solving

Stakeholder management

Tools

Databricks

Spark

Snowflake

Job description

Описание:

Capgemini is an AI-powered global business and technology transformation partner that delivers business value through AI, technology, and people. It provides end-to-end services and solutions across strategy, technology, design, engineering, and business operations.

Задачи:

• Design, develop, and deploy end-to-end Generative AI solutions using LLMs, RAG architectures, and vector databases
• Build and optimize AI-driven applications for document intelligence, compliance automation, and conversational banking solutions
• Develop scalable data pipelines and lakehouse architectures using Databricks, Spark, Snowflake, and cloud-native services
• Integrate structured and unstructured data sources to support advanced analytics and AI use cases
• Deploy, monitor, and manage AI/ML solutions on Azure, AWS, or GCP using MLOps best practices
• Implement CI/CD pipelines, model governance, monitoring, and lifecycle management for AI systems
• Collaborate with business and technology stakeholders to deliver solutions across risk, compliance, trading, fraud detection, and portfolio analytics
• Ensure adherence to regulatory, data privacy, and security standards including GDPR, AML, KYC, and financial services governance requirements
• Establish data governance, lineage, quality, and Responsible AI frameworks covering explainability, bias mitigation, and auditability
• Build and maintain APIs, microservices, and cloud-native platforms supporting enterprise AI applications
• Drive technical architecture decisions, mentor engineering teams, and promote engineering best practices
• Evaluate emerging AI technologies and recommend innovative solutions to enhance business outcomes in financial services

Требования:

• 7+ Years of experience in Data Engineering, AI Engineering, or Machine Learning platforms
• Strong expertise in Python, SQL, GenAI frameworks, cloud platforms, and distributed data processing
• Proven experience delivering AI/Data solutions within Banking, Capital Markets, Insurance, FinTech, or regulated financial environments
• Experience leading teams, mentoring engineers, and driving enterprise-scale technology initiatives
• Strong problem-solving, analytical, and troubleshooting capabilities
• Ability to translate complex business requirements into scalable data and AI solutions
• Excellent communication, presentation, and stakeholder management skills across business and technology teams
• Experience collaborating in Agile/Scrum delivery environments
• Strong understanding of Generative AI, LLMs, RAG architectures, embeddings, and vector databases
• Hands-on expertise in Python, SQL, Spark/PySpark, Databricks, and cloud-native data platforms
• Experience building and deploying APIs, microservices, and cloud-based AI applications
• Knowledge of MLOps, CI/CD, model monitoring, governance, and Responsible AI practices
• Understanding of financial services processes, regulatory requirements, and data privacy frameworks
• Experience mentoring engineers, leading technical initiatives, and driving best practices across teams
• Candidates who declare a disability and meet the minimum essential criteria will be offered an interview; opt in during the application process

Условия:

• Employee wellbeing support includes trained Mental Health Champions and wellbeing apps such as Thrive and Peppy Training and development opportunities include thinktanks, hackathons, access to 250,000 courses, and external certifications
• Recognised as one of the World’s Most Ethical Companies for 13 consecutive years