Artificial Intelligence Architect (8-10 yrs)

AI Architect - Agentic AI

Location : Bengaluru, India

Experience : 8-10 years.

Industry : US Healthcare

Role Overview :

We are seeking a highly skilled AI Architect with expertise in Agentic AI architectures to lead. the design and development of multi-agent AI frameworks. The ideal candidate should have deep knowledge of AI frameworks, LLMs (Large Language Models), transformers, and AI agent ecosystems. You will be responsible for architecting AI-driven solutions in the US healthcare space, ensuring seamless AI-agent interactions, and driving the next generation of autonomous. AI systems.

Key Responsibilities :

- Architect and design Agentic AI frameworks for real-world business use cases in the US healthcare domain

- Develop and implement multi-agent AI ecosystems that leverage LLMs and transformer-based architectures.

- Optimize AI workflows by integrating multi-agent coordination, knowledge sharing, and decision-making processes.

- Work with stakeholders to define AI strategy, technical architecture, and roadmap for AI-driven healthcare solutions.

- Evaluate, experiment, and implement state-of-the-art AI frameworks to improve scalability and performance.

- Ensure compliance with AI governance, security, and ethical AI practices, particularly in healthcare regulatory frameworks (HIPAA, PHI security, etc.)

- Collaborate with AI researchers, data scientists, and ML engineers to enhance model performance

- Stay updated with cutting-edge AI advancements and continuously refine AI frameworks.

Must have skills :

- Agentic AI frameworks (LangChain, AutoGPT, CrewAI, etc.) LLMs and Transformers (GPT, BERT, Claude, Mistral, etc.).

- Multi-agent AI systems and AI orchestration.

- Prompt engineering and LLM fine-tuning.

- Retrieval-Augmented Generation (RAG) and embeddings.

- Python and AI/ML frameworks (PyTorch, TensorFlow, Hugging Face).

- Cloud AI services (AWS/GCP/Azure).

- Vector databases (FAISS, Pinecone, Weaviate, ChromaDB) MLOps, AI model deployment, and pipeline automation.

Good-to-Have Skills :

- Graph databases (Neo4j, ArangoDB).

- Multi-modal AI models (text, vision, speech).

- Reinforcement learning and AI agent self-improvement mechanisms.

- Explainable AI (XAI) and responsible AI frameworks