Opening for Tech Lead-Java in Bangalore

Yrs of Exp: 5 - 7

Location-Bangalore

Mode of Work-Work from office (Monday to Friday)

Mode of Interview- First round-Virtual (if you get selected then

Second round-F2F

JD

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

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

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

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

Development & Integration

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

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

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

Cloud, Deployment & DevOps (AWS)

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

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

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

Security & Compliance (Security-by-Design)

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

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

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

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

AI/ML Integration

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

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

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

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

Leadership & Collaboration

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

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

· Document architectures, runbooks, and playbooks; communicate crisply with technical and non-technical stakeholders.

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Required Skills & Qualifications

Core Stack

· Java (8+), Spring Boot, Hibernate/JPA, REST/gRPC, Maven/Gradle.

· Microservices & distributed systems, API gateway patterns, service mesh (Istio/Envoy) exposure is a plus.

· Datastores: PostgreSQL/MySQL, MongoDB, Redis; understanding of query optimization and indexing.

· Messaging/Streaming: Kafka/RabbitMQ/AWS SQS/Kinesis.

· AWS: EC2, ECS/EKS, Lambda, S3, API Gateway/ALB, CloudWatch/CloudTrail, IAM, Secrets Manager, KMS/HSM.

· DevOps: Git, CI/CD (GitLab/Jenkins/GitHub Actions), Docker, IaC (CloudFormation/Terraform), SonarQube, artifact repositories.

Security

· Hands-on with OAuth2/OIDC/JWT, RBAC/ABAC, hashing & encryption, audit logging, secrets management, and key rotation.

· Familiarity with PCI DSS/SOC 2/ISO 27001 controls or similar financial-grade security frameworks.

AI/ML

· Practical exposure integrating ML models into production services (model endpoints, latency SLAs, monitoring).

· Understanding of classification/anomaly detection for fraud use cases; basics of drift/feedback loops and feature stores.

Professional

· 5–7 years total experience with at least 2–3 years in a technical-lead capacity.

· Proven delivery of high-availability SaaS in payments/fintech or adjacent high-risk domains.

· Strong problem-solving, system thinking, and stakeholder communication.

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Nice to Have

· Experience with graph databases/analytics (e.g., Neo4j/Amazon Neptune) for entity linkage.

· Knowledge of data pipelines/lakes (Glue, EMR, Athena) and BI tooling for risk analytics.

· Certifications: AWS Solutions Architect/DevOps Engineer; security certifications are a plus.

Regards

Valar

Job Type: Full-time

Pay: Up to ₹2,400,000.00 per year

Work Location: In person