Genai / Ai Platform Architect

**Additional Locations**: India-Haryana, Gurgaon

**Diversity - Innovation - Caring - Global Collaboration - Winning Spirit - High Performance**

At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing - whatever your ambitions.

**GenAI / AI Platform Architect**

Join Boston Scientific at the forefront of innovation as we embrace AI to transform healthcare and deliver cutting‑edge solutions. We are seeking an experienced GenAI / AI Platform Architect to define, build, and continuously improve a secure, governable, and enterprise‑grade Generative‑AI platform that underpins copilots, RAG search, intelligent document processing, agentic workflows, and other high‑value use cases.

**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.

**Requisition ID**:608452