Boston Scientific Senior Engineer - Agentic AI 

India, Haryana, Gurugram 

117803856

India-Haryana, Gurgaon

Senior Engineer - Agentic AI

Join Boston Scientific at the forefront of innovation as we embrace AI to transform healthcare and deliver cutting‑edge solutions. As a Principal / Senior Engineer – Agentic AI, you will architect and deliver autonomous, goal‑driven agents powered by large language models (LLMs) and multi‑agent frameworks.

Your responsibilities will include:

• Design and implement agentic AI systems leveraging LLMs for reasoning, multi‑step planning, and tool execution.
• Evaluate and build upon multi‑agent frameworks such as LangGraph, AutoGen, and CrewAI to coordinate distributed problem‑solving agents.
• Develop context‑handling, memory, and API‑integration layers enabling agents to interact reliably with internal services and third‑party tools.
• Create feedback‑loop and evaluation pipelines (LangSmith, RAGAS, custom metrics) that measure factual grounding, safety, and latency.
• Own backend services that scale agent workloads, optimize GPU / accelerator utilization, and enforce cost governance.
• Embed observability, drift monitoring, and alignment guardrails throughout the agent lifecycle.
• Collaborate with research, product, and security teams to translate emerging agentic patterns into production‑ready capabilities.
• Mentor engineers on prompt engineering, tool‑use chains, and best practices for agent deployment in regulated environments.

Required Qualifications:

• 8+ years of software engineering experience, including 3+ years building AI/ML or NLP systems.
• Expertise in Python and modern LLM APIs (OpenAI, Anthropic, etc.), plus agentic orchestration frameworks (LangGraph, AutoGen, CrewAI, LangChain, LlamaIndex).
• Proven delivery of agentic systems or LLM‑powered applications that invoke external APIs or tools.
• Deep knowledge of vector databases (Azure AI Search, Weaviate, Pinecone, FAISS, pgvector) and Retrieval‑Augmented Generation (RAG) pipelines.
• Hands‑on experience with LLMOps: CI/CD for fine‑tuning, model versioning, performance monitoring, and drift detection.
• Strong background in cloud‑native micro‑services, security, and observability.

Preferred Qualifications:

• Experience integrating multimodal agents (vision, audio) and reinforcement‑learning feedback loops. • Contributions to open‑source agent frameworks or white papers on autonomous AI.
• Certifications in cloud GenAI services (AWS Bedrock, Azure OpenAI).
• Domain knowledge of healthcare, cybersecurity, or other regulated industries.