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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
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