GEN AI Developer
capgemini
Job Description
- 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.
- Experience with vector databases and LLM integration workflows.
- 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.
- Experience with API management, enterprise integration patterns, data flows, and compliance architectures.
- 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
- Experience implementing observability, monitoring, and governance for AI applications.
- Strong understanding of NLP and Large Language Models including:
- OpenAI
- Azure OpenAI
- Amazon Bedrock
- Claude
- Other Foundation Models
Preferred Skills
- Experience with AI agents, multi-agent systems, and autonomous workflows.
- Familiarity with model fine-tuning, prompt engineering, and model evaluation techniques.
- Knowledge of MLOps, LLMOps, and AI lifecycle management.
- Experience with Kubernetes, Docker, CI/CD pipelines, and cloud-native architectures.
- Exposure to Responsible AI, AI governance, and regulatory compliance frameworks.
- Experience working with enterprise AI transformation programs.
Soft Skills
- 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.
In this role, you will:
- 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.