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.
Inclusion statement
Присоединяйтесь к Dassault Systèmes, компании 3DEXPERIENCE Сompany Виртуальными вселенными 3DEXPERIENCE компании Dassault Systèmes все становится возможным! Мы обслуживаем 230 000 клиентов в 11 отраслях: от высоких технологий и моды до естественных наук и транспорта... Мы помогаем предприятиям и людям во всем мире создавать устойчивые инновации с учетом потребностей сегодняшнего и завтрашнего дня. Присоединяйтесь к быстрорастущей компании-лидеру, где работает около 20 000 талантливых специалистов.
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