Capgemini
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Bengaluru · On-site · 12+ Yrs · Aug 14
Enterprise Software & Network Solutions · 10000+ Employees · Paris, France
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of €22.5 billion. Capgemini in India comprises nearly 175,000 team members working across 13 locations: Bangalore, Bhubaneswar, Chennai, Coimbatore, Gandhinagar, Gurugram, Hyderabad, Kolkata, Mumbai, Noida, Pune, Salem and Tiruchirappalli. Get The Future You Want | Learn more about Capgemini in India at www.capgemini.com/in-en.
Hiring: Engineering
What employees say
+ Good company to begin your career as a fresher and retire as an experienced professional
− Not a good org in the middle band, as limited career growth opportunities and pay hike is minimal as compared to market standards
More reviews on the company profile.
Interview experience · Senior Consultant
I attended a walk in interview drive. The arrangement was good and the panel was knowledgeable. The questions were moderately difficult and there was two technical rounds, followed by a HR round.
Average difficulty · India · 17,487 reports
More interview insightsJob description
Overview
As a GenAI Architect, you will be responsible for defining scalable GenAI architectures, building reusable assets and accelerators, and collaborating with business and delivery teams to industrialize AI solutions across multiple domains and customer engagements.
Responsibilities
- 12+ years of experience in software architecture, AI/ML, or digital engineering with significant exposure to Generative AI solutions.
- Strong expertise in designing and implementing GenAI architectures and AI solution platforms.
- Hands-on experience with Agentic AI frameworks and intelligent workflow orchestration.
- Strong understanding of Retrieval-Augmented Generation (RAG) architectures and implementation patterns.
- Architect scalable, secure, and modular Generative AI solutions across enterprise and embedded ecosystems.
- Design and develop reusable AI assets, accelerators, and proof-of-concepts (POCs) that can be industrialized for project deployments.
- Define technology roadmaps and identify emerging AI tools, frameworks, and platform capabilities.
- Collaborate closely with business, delivery, and engineering teams to translate business requirements into AI-driven solutions.
- Design and implement Agentic AI architectures leveraging autonomous workflows and orchestration frameworks.
- Support prompt orchestration, model integration, fine-tuning, observability, evaluation, and toolchain automation.
- Develop and optimize Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge sources.
- Architect microservices-based AI platforms and integrations across cloud and enterprise systems.
- Collaborate with data scientists and AI engineers to operationalize machine learning and Generative AI models.
- Establish governance, compliance, security, and monitoring frameworks for AI deployments.
- Drive innovation by evaluating emerging LLMs, foundation models, and AI service offerings.
Qualifications
- Expertise in integrating AI services into enterprise and embedded products.
- Strong experience in microservices architecture and distributed systems design.
- Proficiency in Python, Rust, or .NET development.
- Expertise in cloud platforms including Azure and AWS.
- Strong hands-on experience with orchestration frameworks such as:
- LangChain
- Semantic Kernel
- LlamaIndex
- Similar AI orchestration frameworks
- Strong understanding of NLP and Large Language Models including:
- OpenAI
- Azure OpenAI
- Amazon Bedrock
- Claude
- Other Foundation Models
- Familiarity with model fine-tuning, prompt engineering, and model evaluation techniques.
- Knowledge of MLOps, LLMOps, and AI lifecycle management.
- Exposure to Responsible AI, AI governance, and regulatory compliance frameworks.
- Strong leadership and solution architecture capabilities.
- Excellent stakeholder management and customer-facing skills.
- Strong communication and presentation skills.
- Ability to influence technical and business decision-making.
- Proactive and innovation-driven mindset.
- Strong collaboration skills across cross-functional and global teams.
- Ability to work in fast-paced, evolving technology environments.
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