AI Engineer – GenAI & Multi-Agent Systems

About the role

We are seeking a highly skilled AI Engineer specializing in Generative AI and Multi‑Agent Systems to design, build, and deploy autonomous, LLM‑powered solutions that can reason, collaborate, and execute complex workflows across enterprise environments.

Key responsibilities

• Design and implement multi‑agent AI architectures capable of planning, reasoning, and task execution.
• Develop applications using large language models (GPT, Claude, Llama, etc.) with advanced prompt engineering and orchestration.
• Create Agentic workflows such as planner → executor → critic → memory loops.
• Build Retrieval‑Augmented Generation (RAG) pipelines with vector databases for enterprise knowledge grounding.
• Integrate tool‑using agents with APIs, databases, and other enterprise systems.
• Architect and deploy AI copilots and autonomous assistants for business processes.
• Optimize LLM performance through fine‑tuning, prompt chaining, and caching strategies.
• Implement short‑term and long‑term memory mechanisms using vector stores and knowledge graphs.
• Design multi‑agent collaboration protocols (hierarchical, swarm, role‑based).
• Deploy scalable solutions using MLOps/LLMOps practices, including monitoring, evaluation, and guardrails.

Required profile

• Bachelor’s or Master’s degree in Computer Science, AI, or a related field.
• 3–8 years of hands‑on experience in AI/ML with a strong focus on Generative AI.
• Proficient Python development skills.
• Experience with cloud platforms (Azure OpenAI preferred; AWS or GCP acceptable).

Required skills

• LLM frameworks: OpenAI, Hugging Face Transformers.
• Agent frameworks: LangChain, AutoGen, CrewAI, Semantic Kernel.
• RAG pipelines and vector databases: FAISS, Pinecone, Weaviate.
• Containerization and orchestration: Docker, Kubernetes.
• CI/CD pipelines and related DevOps tools.