Company: ITTStar Global Services Pvt Ltd

Website: Visit Website

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Business Type: Small/Medium Business

Company Type: Product & Service

Business Model: B2B

Funding Stage: Bootstrapped

Industry: Information Technology

Salary Range: ₹ 15-25 Lacs PA

We are seeking a Senior Data Scientist specializing in Agentic AI to design, build, and deploy production-grade autonomous multi-agent systems across regulated Fintech and Healthcare environments . The role involves developing intelligent agent workflows for fraud detection, credit underwriting, clinical decision support, and medical summarization, while ensuring compliance, explanability, and operational reliability.

Experience: 7–9 years | Domains: Fintech + Healthcare (both mandatory)

- Design and deploy production-grade autonomous multi-agent systems using LangGraph, AutoGen, and CrewAI for fraud detection, loan underwriting, patient risk stratification, and clinical summarization workflows.
- Build tool-using LLM agents that autonomously invoke credit bureau APIs, FHIR patient records, sanctions databases, and drug interaction databases via MCP (Model Context Protocol) and structured function calling.
- Engineer production RAG pipelines grounded on RBI/SEBI regulations, PCI-DSS policies, HIPAA guidelines, and clinical protocols - enabling agents to cite evidence and explain decisions to auditors and clinicians.
- Enforce structured, schema-validated agent outputs using Instructor or Outlines for reliable integration into downstream financial transaction and clinical EHR systems.
- Build real-time feature pipelines on Kafka and Flink feeding agent decision loops with sub-100ms latency for fraud alerting and patient deterioration detection.
- Develop and maintain classical ML models -XGBoost,



LightGBM, Cox PH survival analysis — with full SHAP and LIME explanability reports for RBI/SEBI risk committees and clinical governance boards.
- Implement persistent agent memory using Mem0, Zep, or vector stores (Pinecone, Weaviate, pgvector) and design self-critique reflection loops for output quality and compliance validation.
- Fine-tune foundation models using QLoRA and PEFT on proprietary fintech transaction data and de-identified clinical notes for entity extraction, classification, and report generation.
- Instrument full agent traces using LangSmith or Langfuse; own CI/CD pipelines via GitHub Actions and MLflow with automated regression testing before every production deployment.
- Implement responsible AI guardrails using NeMo Guardrails and PHI de-identification pipelines via Microsoft Presidio ensuring HIPAA, DISHA, and PCI-DSS compliance across all data flows.
- Monitor model and agent drift using Evidently AI or NannyML; design agents that autonomously trigger retraining workflows or human escalation when confidence thresholds are breached.
- Partner directly with Chief Risk Officers, compliance teams, ICU physicians, and hospital administrators to translate domain policies and clinical hypotheses into agent workflows.
- Hands-on expertise required across LangChain, LangGraph, AutoGen, PyTorch, HuggingFace, Kafka, Spark, dbt, Kubernetes, Ray Serve, AWS SageMaker, and GCP Vertex AI.
- Deep domain fluency mandatory in fintech risk frameworks (fraud, AML, credit) and healthcare data standards (HL7 FHIR, OMOP CDM, Clinical NLP, FDA SaMD).
- Must have at least one autonomous agentic system shipped to production in a regulated setting; ability to mentor junior data scientists and define team-wide agentic AI standards expected.

📌 Senior Data Scientist (Bengaluru)
🏢 ICE
📍 Bengaluru