Shashanka Raj Srivastava
Shashanka Raj Srivastava
About
Detail
GenAI Architect | Data Science Manager | MLOps | LLM & RAG Infrastructure | AWS & Databricks | 9+ Yrs Applied ML
Maharashtra, India
I architect the boring infrastructure that makes GenAI actually work in production—and lead the engineers who ship it.
Currently, I'm a Data Science Manager II at MSD, building enterprise GenAI copilots and MLOps platforms used by thousands of internal users across US and global markets. Over my 9-year career across TCS, Marlabs, and MSD, I've evolved from training models in notebooks to owning the full path from
data discovery → architecture review → production deployment in highly regulated environments.
🛠 What I'm known for:
Productionizing GenAI: Turning experimental notebooks into containerized, tested, and monitored services that run reliably for thousands of daily users. I recently shipped multiple Enterprise Copilots, maintaining full lifecycle ownership from data discovery and SIT to business handoff.
Audit-Ready MLOps: Building CI/CD pipelines with code quality gates, automated testing, controlled environment promotion, and traceable model lineage. In pharma, you cannot ship without this; most teams underestimate how much it slows them down later.
RAG Architecture at Scale: Designing vector stores (Qdrant, PgVector), retrieval evaluation patterns, and inference architectures that work on 600+ GB datasets—not toy demos. I've standardized our internal RAG patterns, which are now reused across multiple copilot products.
Architecture Governance: Presenting and defending AI architecture proposals at MSD's Architecture Review Board (ARB), securing production approvals for systems serving thousands of users in strict, regulated business domains.
🧰 The Stack I Reach For Daily:
Core: Python, Docker, Kubernetes, Terraform, GitHub Actions, Temporal
Cloud & Infrastructure: Databricks (Unity Catalog, Genie, Workflows), AWS (SageMaker, EKS, Step Functions, ECR), GCP, Azure DevOps
Data & AI Platforms: Databricks (Genie, Unity Catalog), Qdrant, PgVector
🎓 Education & Certifications:
BE in Computer Science | MS in Machine Learning (partial) - NIT Trichy
HashiCorp Terraform Certified
GCP Cloud Developer
DeepLearning.AI Neural Networks
Microsoft ML Scholarship Recipient
🤝 What I'm Open To:
→ Senior IC Architect roles (Principal/GenAI Engineer, AI Architect)
→ Engineering Management roles (Sr. Manager)
→ Selective advisory or fractional architecture consulting in pharma/life-sciences AI
If you're building production GenAI in healthcare, life sciences, or other regulated domains where reliability matters as much as model accuracy—I'd be happy to talk.
📩 Reach me at: shashankraj07@gmail.com or via LinkedIn DM.
Currently, I'm a Data Science Manager II at MSD, building enterprise GenAI copilots and MLOps platforms used by thousands of internal users across US and global markets. Over my 9-year career across TCS, Marlabs, and MSD, I've evolved from training models in notebooks to owning the full path from
data discovery → architecture review → production deployment in highly regulated environments.
🛠 What I'm known for:
Productionizing GenAI: Turning experimental notebooks into containerized, tested, and monitored services that run reliably for thousands of daily users. I recently shipped multiple Enterprise Copilots, maintaining full lifecycle ownership from data discovery and SIT to business handoff.
Audit-Ready MLOps: Building CI/CD pipelines with code quality gates, automated testing, controlled environment promotion, and traceable model lineage. In pharma, you cannot ship without this; most teams underestimate how much it slows them down later.
RAG Architecture at Scale: Designing vector stores (Qdrant, PgVector), retrieval evaluation patterns, and inference architectures that work on 600+ GB datasets—not toy demos. I've standardized our internal RAG patterns, which are now reused across multiple copilot products.
Architecture Governance: Presenting and defending AI architecture proposals at MSD's Architecture Review Board (ARB), securing production approvals for systems serving thousands of users in strict, regulated business domains.
🧰 The Stack I Reach For Daily:
Core: Python, Docker, Kubernetes, Terraform, GitHub Actions, Temporal
Cloud & Infrastructure: Databricks (Unity Catalog, Genie, Workflows), AWS (SageMaker, EKS, Step Functions, ECR), GCP, Azure DevOps
Data & AI Platforms: Databricks (Genie, Unity Catalog), Qdrant, PgVector
🎓 Education & Certifications:
BE in Computer Science | MS in Machine Learning (partial) - NIT Trichy
HashiCorp Terraform Certified
GCP Cloud Developer
DeepLearning.AI Neural Networks
Microsoft ML Scholarship Recipient
🤝 What I'm Open To:
→ Senior IC Architect roles (Principal/GenAI Engineer, AI Architect)
→ Engineering Management roles (Sr. Manager)
→ Selective advisory or fractional architecture consulting in pharma/life-sciences AI
If you're building production GenAI in healthcare, life sciences, or other regulated domains where reliability matters as much as model accuracy—I'd be happy to talk.
📩 Reach me at: shashankraj07@gmail.com or via LinkedIn DM.
Contact Shashanka regarding:
work
Full-time jobs