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AI Architect
Job Description
Job Description
AI Solution Architect
Experience: 10–18 Years
Choosing Capgemini means joining a global leader in business and technology transformation, where innovation, collaboration, and cutting-edge technologies come together to create meaningful impact. Join us to help leading manufacturing and industrial organizations accelerate their Industry 4.0 and AI transformation journeys.
Role Overview
We are seeking an experienced Industrial AI Solution Architect to lead the design and delivery of AI-driven solutions for manufacturing and industrial clients. This role combines industry expertise, AI innovation, solution architecture, consulting, and business transformation to drive measurable operational outcomes.
Key Responsibilities
Education
At Capgemini Engineering, we bring together industry experts, engineers, architects, and technologists to help organizations harness innovation and achieve sustainable business outcomes. Our expertise spans Digital Manufacturing, AI, Data, Cloud, and Industry 4.0, enabling clients to transform operations and unlock new business value.
AI Solution Architect
Experience: 10–18 Years
Choosing Capgemini means joining a global leader in business and technology transformation, where innovation, collaboration, and cutting-edge technologies come together to create meaningful impact. Join us to help leading manufacturing and industrial organizations accelerate their Industry 4.0 and AI transformation journeys.
Role Overview
We are seeking an experienced Industrial AI Solution Architect to lead the design and delivery of AI-driven solutions for manufacturing and industrial clients. This role combines industry expertise, AI innovation, solution architecture, consulting, and business transformation to drive measurable operational outcomes.
Key Responsibilities
- Ability to lead AI solution architecture, client engagements, and AI transformation initiatives.
- Strong expertise in Generative AI, LLMs (GPT, Claude, Gemini, Llama), and Prompt Engineering
- Hands-on experience building Agentic AI and Multi-Agent Systems using CrewAI, AutoGen, LangGraph, or Semantic Kernel.
- Proficiency in Python, FastAPI, REST APIs, and Microservices architecture.
- Strong knowledge of RAG, Vector Databases, Embeddings, and Enterprise Knowledge Systems.
- Experience with Azure OpenAI, Azure AI Services, AWS Bedrock, and cloud-based AI platforms
- Understanding of AI governance, observability, security, and responsible AI practices.
Education
- Bachelor's or Master's degree in Engineering, Computer Science, Industrial Engineering, Data Science, or a related field.
- 7+ years of experience in Manufacturing, Industrial Operations, Digital Manufacturing, Industry 4.0, or Industrial Digital Transformation.
- 3+ years of experience designing and deploying AI, Machine Learning, Advanced Analytics, or Generative AI solutions.
- AI solutions successfully deployed into production.
- Measurable client outcomes such as productivity improvement, cost reduction, quality enhancement, and operational efficiency gains.
- Growth of AI-driven business pipeline and revenue.
- Development of reusable assets and industrial AI accelerators.
- Increased adoption of AI across manufacturing and industrial operations.
- Client satisfaction and executive stakeholder trust.
- A visionary technology leader who understands both the factory floor and the AI frontier—capable of transforming industrial operations through scalable, responsible, and outcome-driven AI solutions.
At Capgemini Engineering, we bring together industry experts, engineers, architects, and technologists to help organizations harness innovation and achieve sustainable business outcomes. Our expertise spans Digital Manufacturing, AI, Data, Cloud, and Industry 4.0, enabling clients to transform operations and unlock new business value.
More Info
Key Skills
AWS Bedrock
Claude
Azure OpenAI
GPT
Microservices architecture
LangGraph
Vector Databases
Embeddings
Multi-Agent Systems
cloud-based AI platforms
responsible AI practices
observability
CrewAI
Generative AI
Enterprise Knowledge Systems
LLMs
Semantic Kernel
AutoGen
Azure AI Services
Agentic AI
Llama
RAG
AI governance
Prompt Engineering
About Company
Skills:
Machine Learning, Nodejs, Tensorflow, Nosql, Nlp, Pytorch, Docker, Python, Java, Sql, Deep Learning, MLops, Kubernetes, HuggingFace, Lang Chain, Azure OpenAI, RAG architectures, Generative AI, LLMs, Anthropic, prompt engineering, CI/CD, OpenAI, LlamaIndex
Skills:
Saml, Kafka, Spring Boot, Microservices, Nosql, Spring Security, AWS, Oauth, Java, J2EE, Spring MVC, Sql, Rabbitmq, Gcp, MLops, DevSecOps, Restful Apis, Azure, Prompt engineering, Event-driven architecture, Pinecone, semantic search, Azure AI Search, Generative AI, LLMs, LLMOps, Ai, FAISS, RAG, Knowledge graphs, Weaviate, OIDC
Skills:
Machine Learning Algorithms, Python, Agentic AI Framework Crew AI AutoGen LangGraph Google AVD, RAG Multimodal Architecture using Langchain LlamIndex, LLMs, Data Visualization Tools, Knowledge Graph implementation, MCP Architecture, Fine tuning of LLM, Autoregressive model Decoder GPT BLOOM LLama Mistral Claude CodeGen OPT PaLM, Autoencoding model Encoder ROBERTA BERT DistilBERT, Model deployment LLMOps Scalability and Performance, Transformer Architecture Encoder and decoders, Statistical programming languages, Embedding Models, Prompt Engineering, Langsmith framework
Skills:
Apache Spark, Azure Databricks Delta Lake, Azure AI services, Databricks Genie, Azure Databricks Lakehouse
Skills:
.NET, Azure Sql, REST, Neo4j, Cosmos DB, Azure, Oracle, Python, AWS, Api Management, Apis, Microservices, GenAI, LLMOps, GRPC, ASP.NET Core, AI governance, Map-based or data visualization platforms, Adapters and connectors, RAG, MCP