BP
Full time
🤖 AI / ML
AI / ML Platform Engineer at BNP Paribas
Listed by DevShelfHub
Mumbai, Maharashtra, India
Hybrid
Senior · 7–9 yrs
About the Role
Financial crime detection platforms need AI/ML platform engineers who can productionize graph analytics, LLM pipelines, and ML models for AML compliance. BNP Paribas is hiring an AI / ML Platform Engineer in Mumbai for its AML IT platform.
What you'll do
- You will turn advanced ML research into production-grade AML detection solutions.
- Build and maintain large-scale knowledge graphs with ETL, entity resolution, and GNN feature jobs
- Create end-to-end LLM pipelines with vector DB, prompt engineering, and multi-agent reasoning
- Own non-ML microservices: Alert Service, Case Manager, API Gateway, deduplication, rule-engine integration
- Ensure high-throughput, low-latency event-driven processing with Kafka, PostgreSQL, Redis
- Apply CI/CD, MLflow, testing, monitoring, model governance, and audit logging
- Manage on-prem Kubernetes ecosystem with Helm, ArgoCD, GPU scheduling
- Handle Spark/PySpark, Flink/Kafka Streams, dbt, Terraform/Pulumi, observability stack
- Collaborate with data-science, compliance, and investigation teams globally
What we're looking for
- At least 7 years experience; Bachelor's degree or equivalent
- Production-grade ML models: GNNs, LLMs, RAG pipelines with AML governance
- Knowledge graphs: Neo4j/Cypher, graph-ETL, PyG/DGL frameworks
- LLM: LangChain/LangGraph, prompt engineering, vector DB (Pinecone, pgvector, Weaviate)
Skills & Technologies
Required
At least 7 years experience; Bachelor's degree or equivalent
Production-grade ML models: GNNs, LLMs, RAG pipelines with AML governance
Knowledge graphs: Neo4j/Cypher, graph-ETL, PyG/DGL frameworks
LLM: LangChain/LangGraph, prompt engineering, vector DB (Pinecone, pgvector, Weaviate)
Backend microservices and API integration for ML outputs
Kafka, PostgreSQL, Redis, Docker deployments
Kubernetes, Helm, ArgoCD GitOps
Spark/PySpark, Flink/Kafka Streams, dbt, Terraform/Pulumi
Benefits & Perks
- Health Insurance
- Flexible Leave Policy
- Learning Budget
- EPF / NPS
Why This Role is Good for Experienced Professionals
- This role is the technical cornerstone linking graph analytics, LLM reasoning, ML outputs, and cloud-native infrastructure for next-generation AML detection.
- Build large-scale knowledge graphs for GNN models scoring shell companies and sanctions proximity
- Create LLM pipelines with vector embeddings, multi-agent reasoning, and narrative generation
- Own microservices making ML outputs actionable (Alert Service, Case Manager, API Gateway)
- High-throughput event-driven processing with Kafka, PostgreSQL, Redis, Docker
- CI/CD, MLflow, automated testing, model governance, audit logging
- Manage on-prem Kubernetes (Helm, ArgoCD GitOps, GPU scheduling)
- Apache Spark/PySpark, Flink/Kafka Streams, dbt, Terraform/Pulumi IaC
- Observability: Prometheus-Grafana, ELK stack
- Reference: 612345678901012516
About BNP Paribas
BNP Paribas is the European Union's leading bank. The AML IT function within Corporate & Institutional Banking (CIB) CEFS-technology provides end-to-end technology enabling the bank's anti-money-laundering program, transforming transaction data into actionable AML intelligence across global operations.
- Industry
- Technology
- Company Size
- 500+
- Website
- bnpparibas.com
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Job Details
- Type
- Full time
- Level
- Senior
- Experience
- 7–9 years
- Location
- Mumbai, Maharashtra, India
- Work Mode
- Hybrid
- Category
- AI / ML
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