Senior AI Engineer

2

2070Health

Bengaluru, Karnataka, India

Permanent - Full Time

ML/Data Science

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About 2070 Health

2070 Health is India’s first Venture Studio dedicated to building transformative, patient-centric healthcare companies from scratch. We identify disruptive opportunities, partner with exceptional founders, and leverage our innovation platform and playbooks to co-create and scale solutions that address critical healthcare needs in India.

Role Overview

We are seeking a Senior AI Engineer with a deep understanding of AI and ML, extensive experience in building and deploying large language model (LLM) agents, and a passion for solving real-world healthcare challenges. You will architect, develop, and optimize AI agents using LLMs for varied use cases across our portfolio startups, collaborating closely with founders, product, and engineering teams to deliver robust, scalable, and ethical AI-driven solutions that directly impact patient outcomes and operational efficiency.

Key Responsibilities

• AI Agent Development: Architect, build, and maintain autonomous AI agents using state-of-the-art LLM frameworks (e.g., LangChain, CrewAI, LlamaIndex) for healthcare and operational automation.
• Prompt Engineering & Orchestration: Design advanced prompt strategies, tool integrations, and agent workflows to enable complex reasoning, task automation, and multi-step interactions.
• Model Integration & Fine-tuning: Integrate, fine-tune, and optimize LLMs for domain-specific tasks, ensuring high accuracy, safety, and compliance with healthcare standards.
• Data Pipeline & Infrastructure: Develop and maintain robust data pipelines for agent training, evaluation, and continuous improvement, ensuring data privacy and governance.
• Collaboration: Work closely with product managers, engineers, clinical experts, and founders to define requirements, iterate on solutions, and ensure seamless integration of AI agents into products.
• Monitoring & Maintenance: Implement real-time monitoring, performance tracking, and automated retraining pipelines to ensure reliability and continuous improvement of deployed agents.
• Ethical & Responsible AI: Champion responsible AI development by addressing bias, transparency, and explainability, especially in regulated healthcare environments.
• Documentation & Knowledge Sharing: Document best practices, contribute to internal playbooks, and mentor team members on agentic AI systems and LLM technologies.
  
  

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