12 hours ago
Pune, IndiaStaff+
Responsibilities
- Design end-to-end AI systems covering data pipelines, model lifecycle, APIs, and integration layers.
- Architect scalable cloud-native AI solutions using microservices, containers, and distributed computing.
- Integrate AI solutions with ERP, CRM, data platforms, and other enterprise systems.
- Establish MLOps, model versioning, monitoring, and automated deployment strategies.
- Collaborate with data teams on AI-optimized data ingestion, storage, and processing.
- Define technology standards and select tools, frameworks, and platforms for scalability.
- Ensure solutions meet latency, throughput, availability, cost, and SLA requirements.
- Embed security, privacy, governance, and responsible AI principles into solution architecture.
- Translate business requirements into technical architectures and present solutions to leadership.
Requirements
- Expert-level understanding of AI, ML, GenAI, and agentic AI technical solutions and frameworks.
- Advanced working knowledge of AWS, Azure, and GCP, along with agent development.
- Deep understanding of data engineering concepts.
- Knowledge of MLOps, DevOps, and CI/CD best practices.
- Excellent communication and stakeholder management abilities.
Benefits
- Hybrid work arrangements and support for work-life balance.
- Career growth and professional development opportunities.
- Certifications and training programs in GenAI, agentic AI, and other latest technologies.
Tech Stack
Categories
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.