Boston Scientific GenAI / AI Platform Architect 

India, Haryana, Gurugram 

738661083

India-Haryana, Gurgaon

Your responsibilities will include:

• Own the reference architecture for GenAI: LLM hosting, vector DBs, orchestration layer, real‑time inference, and evaluation pipelines.
• Design and govern Retrieval‑Augmented Generation (RAG) pipelines—embedding generation, indexing, hybrid retrieval, and prompt assembly—for authoritative, auditable answers.
• Select and integrate toolchains (LangChain, LangGraph, LlamaIndex, MLflow, Kubeflow, Airflow) and ensure compatibility with cloud GenAI services (Azure OpenAI, Amazon Bedrock, Vertex AI).
• Implement MLOps / LLMOps: automated CI/CD for model fine‑tuning, evaluation, rollback, and blue‑green deployments; integrate model‑performance monitoring and drift detection.
• Embed “shift‑left” security and responsible‑AI guardrails—PII redaction, model‑output moderation, lineage logging, bias checks, and policy‑based access controls—working closely with CISO and compliance teams.
• Optimize cost‑to‑serve through dynamic model routing, context‑window compression, and GPU / Inferentia auto‑scaling; publish charge‑back dashboards for business units.
• Mentor solution teams on prompt engineering, agentic patterns (ReAct, CrewAI), and multi‑modal model integration (vision, structured data).
• Establish evaluation frameworks (e.g., LangSmith, custom BLEU/ROUGE/BERT‑Score pipelines, human‑in‑the‑loop) to track relevance, hallucination, toxicity, latency, and carbon footprint.
• Report KPIs (MTTR for model incidents, adoption growth, cost per 1k tokens) and iterate roadmap in partnership with product, data, and infrastructure leads.

Required Qualifications:

• 10+ years designing cloud‑native platforms or AI/ML systems; 3+ years leading large‑scale GenAI, LLM, or RAG initiatives.
• Deep knowledge of LLM internals, fine‑tuning, RLHF, and agentic orchestration patterns (ReAct, Chain‑of‑Thought, LangGraph).
• Proven delivery on vector‑database architectures (Pinecone, Weaviate, FAISS, pgvector, Milvus) and semantic search optimization.
• Mastery of Python and API engineering; hands‑on with LangChain, LlamaIndex, FastAPI, GraphQL, gRPC.
• Strong background in security, governance, and observability across distributed AI services (IAM, KMS, audit trails, OpenTelemetry).

Preferred Qualifications:

• Certifications: AWS Certified GenAI Engineer – Bedrock or Microsoft Azure AI Engineer Associate.
• Experience orchestrating multimodal models (images, video, audio) and streaming inference on edge devices or medical sensors.
• Published contributions to open‑source GenAI frameworks or white‑papers on responsible‑AI design.
• Familiarity with FDA or HIPAA compliance for AI solutions in healthcare.
• Demonstrated ability to influence executive stakeholders and lead cross‑functional tiger teams in a fast‑moving AI market.