Senior Backend Engineer - Agentic SDLC / AI-Driven Development Lifecycle (AI-DLC) Platform
VirtusaJobsCloseBy Editorial Insights
Virtusa is seeking a Senior Backend Engineer to design and evolve the core backend of its Agentic SDLC / AI-DLC platform in Dubai. The role requires 10+ years of hands-on backend experience in production, plus proven enterprise-scale Agentic SDLC / AI-DLC implementation experience, with a preference for banking or fintech environments. You will own production-grade microservices built with Java 17+ and Spring Boot 3.x, write OpenAPI specifications and Architecture Decision Records, and drive testing with a strong TDD discipline to achieve high coverage. You will design and operate AI agent pipelines, secure MCP integrations with internal systems, and manage event-driven workflows using Kafka and AWS. To apply, tailor your resume to highlight relevant platform work, include measurable outcomes, emphasize compliance and security, and reference CREQ259698.
Description
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)