Engineering Lead

YODLEE ENGINEERING - AI-Enabled Platform

Senior Backend Engineer

Location : India (STG Labs - Dedicated Offshore Pod)

Experience : 8 - 12+ Years

Employment Type : Full-Time

Role Purpose :

Yodlee is establishing a lean, AI-enabled engineering pod in India to accelerate delivery of our Next Generation API and Platform initiatives.

This role combines strong architectural expertise with disciplined AI-assisted development practices to measurably improve productivity, automation maturity, and operational efficiency, while maintaining enterprise-grade quality, security, scalability, and performance standards.

The engineer will own a platform component end-to-end and operate with high accountability in a compact, high-performance team model.

Key Responsibilities :

End-to-End Ownership :

- Drive HLD/LLD architecture and technical design.

- Develop scalable REST/GraphQL APIs and microservices.

- Implement secure authentication & authorization (OpenID Connect, OAuth2, JWT).

- Lead performance optimization and production troubleshooting.

- Support SaaS, multi-tenant, and Canary deployment models.

- Own CI/CD integration and production support (RCA, reliability improvements).

AI-Enabled Engineering :

- Expected to operate at measurably higher productivity through disciplined AI-enabled development practices measured via automation coverage, delivery velocity, and defect leakage metrics.

- Leverage AI coding assistants (e.g., Cursor, GitHub Copilot) for code generation, refactoring, documentation, and test automation.

- Rapidly prototype and compare design approaches using AI.

- Auto-generate and validate unit/integration tests.

- Apply engineering judgment to validate AI-generated outputs.

- Contribute to responsible AI-assisted development best practices.

- Demonstrate measurable productivity improvements through AI-enabled workflows.

Required Technical Skills :

- Backend & APIs : Java (JDK17/21), Spring Boot, Microservices, REST / GraphQL, Event-driven systems (Kafka/SQS), Python (automation).

- Security : OAuth2, JWT, OpenID Connect, Secure coding (OWASP).

- Data : Oracle/PostgreSQL, MongoDB, Redis (caching), Cassandra, Data modeling & optimization.

- Cloud & Platform : AWS (EKS/ECS, Lambda, RDS, S3), Docker, Kubernetes.

- DevOps & Observability : CI/CD (Jenkins/GitHub Actions), Terraform/CloudFormation, Blue-Green/Canary deployments, Logging & Monitoring (Splunk/ELK/Grafana), JVM tuning.

- Core Engineering Fundamentals : Strong Data Structures & Algorithms, Concurrency, System Design (HLD/LLD), High-availability design.

AI Tool Proficiency (Mandatory) :

- Demonstrated enterprise experience using AI coding assistants.

- Ability to validate AI-generated code for correctness, security, and scalability.

- Experience using AI for architecture exploration, debugging, refactoring, and test generation.

- Strong judgment to balance automation with human oversight.

- Ability to mentor engineers in AI-enabled workflows.

Behavioral Expectations :

- Strong ownership mindset.

- Ability to operate independently with minimal supervision.

- Production-grade debugging capability.

- Clear written and verbal communication.

- High accountability in a lean, AI-augmented team model.

- Mentorship capability (SMTS level).

Success Metrics (First 90 Days) :

- Independently own a platform component.

- Deliver production-ready features using AI-assisted acceleration.

- Improve automation coverage and CI/CD efficiency.

- Demonstrate measurable productivity uplift and quality improvements.

- Contribute to platform performance or reliability enhancements.

Education :

BE / B.Tech / MCA / ME / MS in Computer Science or related field.

Skills

Engineering Management, Backend Architecture, GraphQL, Microservices Architecture, SaaS, Java, Spring Boot, Python, AWS, PostgreSQL, MongoDB