AI Engineer – Enterprise AI Platforms & Agentic Systems
- Design, develop, and maintain enterprise AI solutions including autonomous AI agents, MCP servers, enterprise AI skills, orchestration pipelines, and RAG-based knowledge systems.
- Build scalable AI services and frameworks supporting engineering, QA, DevSecOps, and software lifecycle workflows.
- Develop intelligent retrieval systems using vector databases, embeddings, indexing, chunking, semantic search, and context management techniques.
- Integrate and optimize enterprise AI solutions using OpenAI GPT models, AWS Bedrock, LLaMA, Mistral, and open-source LLM ecosystems.
- Collaborate with platform engineers, AI teams, QA teams, and R&D organizations to build secure, scalable, and enterprise-ready AI solutions.
- Research and evaluate emerging advancements in Generative AI, Agentic AI systems, RAG pipelines, and LLM orchestration frameworks.
- Contribute to reusable AI frameworks, engineering standards, and best practices across the organization.
- 2–5 years of hands-on experience in Generative AI, NLP, Machine Learning, backend engineering, or AI platform development.
- Strong programming expertise in Python and SQL with hands-on experience in AI/ML frameworks such as PyTorch or TensorFlow and backend frameworks like FastAPI.
- Practical experience with Large Language Models (LLMs), RAG architectures, Agentic AI workflows, prompt engineering, and AI orchestration frameworks.
- Experience working with OpenAI GPT models, AWS Bedrock, LLaMA, Mistral, or similar enterprise/open-source AI ecosystems.
- Strong understanding of embeddings, vector databases, semantic retrieval, indexing, chunking methodologies, and context management techniques for enterprise AI systems.
- Experience building or integrating MCP servers, AI tools/plugins, API-driven AI systems, and enterprise AI workflows.
- Familiarity with Docker, Git, REST APIs, and CI/CD pipelines.
- Strong analytical, problem-solving, collaboration, and communication skills with ability to work in cross-functional teams.
Good to Have
- Experience with Neo4j, Knowledge Graphs, Kubernetes, Redis, or AI observability platforms.
- Exposure to secure AI engineering, AI governance, and enterprise-scale AI deployment practices.
- Contributions to open-source AI initiatives, hackathons, or research-driven projects.
Education
- BE / B.Tech / MCA / M.Sc or equivalent degree from an accredited university.
Déclaration de diversité
Dassault Systèmes est un accélérateur de progrès humain. Nous proposons aux entreprises et aux particuliers des environnements virtuels collaboratifs permettant d’imaginer des innovations durables. Grâce aux jumeaux virtuels d’expérience du monde réel qu’ils créent avec la plateforme 3DEXPERIENCE et ses applications, Dassault Systèmes est un créateur de valeur, au service de plus de 350,000 clients de toutes tailles et de tous secteurs d’activité, dans plus de 150 pays. Rejoignez notre communauté mondiale de plus de 23,800 personnes passionnées !
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