Senior Backend Engineer - Agentic SDLC / AI-Driven Development Lifecycle (AI-DLC) Platform

Experience & Qualifications:

• 10+ years of professional hands-on backend software engineering experience in production environments — mandatory

• Demonstrated, verifiable enterprise-scale Agentic SDLC / AI-DLC implementation experience — mandatory 

• Experience in banking, fintech, or a similarly regulated, high-compliance domain — strongly preferred

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field (or equivalent professional experience)

• AWS Certified Developer / Solutions Architect — a plus

• Proven track record of delivering complex distributed systems with high availability and measurable performance outcomes

Key Responsibilities:

Agentic SDLC / AI-DLC Platform Engineering

• Design, build, and evolve the core backend infrastructure of Client’s Agentic SDLC / AI-DLC platform 

• Develop and operate AI agent pipelines for spec ingestion, code generation, automated review, and test synthesis

• Build MCP server integrations and tool-use layers that enable AI agents to interact with internal banking systems, APIs, and data sources securely

• Architect and maintain RAG pipelines that ground AI agents in Client’s codebase, API contracts, compliance rules, and architecture decisions

• Establish quality gates and evaluation frameworks that validate AI-generated code against engineering standards before it enters the delivery pipeline

Core Backend Engineering

• Design and build production-grade microservices using Java 17+ and Spring Boot 3.x adhering to clean code and SOLID principles

• Own services end-to-end\: spec → design → implement → test → deploy → monitor → iterate — with no hand-offs

• Author OpenAPI 3.x specifications and Architecture Decision Records (ADRs) before writing code; champion spec-driven development

• Write comprehensive unit, integration, and contract tests using TDD discipline with ≥80% meaningful coverage

• Design and manage event-driven architectures using Apache Kafka for asynchronous workflows, domain events, and data streaming

• Architect and deploy services on AWS (ECS/EKS, Lambda, RDS, S3, SQS/SNS, CloudWatch, IAM)