Technical Lead AI-Powered Fraud & Risk Management Platform - Java

Position: Technical Lead — AI-Powered Fraud & Risk Management Platform

Location: Bengaluru (Bannerghatta Road, JP Nagar) Work Mode: WFO (On-site only) Experience: 5–7 years total (with recent hands-on leadership) Notice Period: 15 days Employment Type: Full-time

Role Summary

Lead the architecture, design, and delivery of an AI-powered Fraud & Risk Management platform built on open-source technologies. You’ll be a hands-on technical lead with deep expertise in Java, Spring Boot, Hibernate, AWS, and microservices, and you’ll embed AI/ML models into real-time risk decisioning while ensuring strong security, compliance, and scalability.

Key Responsibilities

Architecture & Design

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  Define and own a modular, microservices architecture (API-first, domain-driven boundaries) using Java/Spring Boot/Hibernate.

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  Establish service contracts, data models, and event flows (Kafka/SQS/Kinesis) for high-throughput risk evaluation.

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  Drive scalability, resilience, and performance (autoscaling, caching, circuit breakers, rate limiting).

Development & Integration

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  Build and maintain high-performance services and REST/gRPC APIs; enforce clean code, unit/integration tests, and code reviews.

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  Integrate with payment processors, core banking/fintech systems, KYC/AML providers, device intelligence, and graph/analytics layers.

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  Implement observability (CloudWatch/Prometheus/Grafana/OpenTelemetry) and SLOs for latency, availability, and error budgets.

Cloud, Deployment & DevOps (AWS)

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  Design secure AWS topologies (VPC, subnets, NACLs, Security Groups, IAM), containerize with Docker and orchestrate via ECS/EKS.

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  Own CI/CD (GitLab/Jenkins/GitHub Actions), blue/green and canary releases, infrastructure as code (CloudFormation/Terraform).

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  Optimize cost and performance (autoscaling policies, right-sizing, storage tiers).

Security & Compliance (Security-by-Design)

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  Implement authentication/authorization (OAuth2/OIDC, JWT), RBAC/ABAC for permissions and roles.

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  Enforce encryption & hashing (TLS 1.2+/1.3, AES-256 at rest, PBKDF2/bcrypt/Argon2 for secrets), secure secrets rotation.

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  Integrate AWS KMS / HSM for key management; implement comprehensive audit logging and tamper-evident trails.

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  Champion secure SDLC: threat modeling, SAST/DAST/IAST, dependency scanning, SBOMs, vulnerability remediation.

AI/ML Integration

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  Partner with data scientists to ingrain AI into the solution: define model-serving interfaces (REST/gRPC), latency budgets, and fallbacks.

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  Contribute to feature engineering, training data specs, and model evaluation (precision/recall, ROC-AUC, drift detection).

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  Implement MLOps pipelines (versioning, A/B & shadow tests, monitoring, rollback), and ensure explainability where required (e.g., SHAP/LIME).

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  Translate model outputs into deterministic risk rules and reason codes for regulator-friendly decisions.

Leadership & Collaboration

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  Mentor a team of backend engineers; set coding standards, review designs, and resolve complex production issues.

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  Work closely with Product, QA, DevOps, Data, and Security to deliver roadmap commitments on time with quality.