Full Stack Developer
VirtusaJobsCloseBy Editorial Insights
Virtusa is seeking a Full Stack Developer in Sydney for a Senior/Staff track, requiring 6+ years for Senior Software Engineer or 10+ years for Staff Engineer Lead. The role demands hands on AWS experience (EC2, Lambda, DynamoDB, S3) plus Kinesis, Firehose, CloudWatch, Aurora, Step Functions, CDK and CloudFormation. Proficiency in TypeScript/Node.js/Next.js is preferred, or C#/.Net; you will design APIs and service contracts for distributed microservices and support event driven architectures with CI/CD and IaC pipelines. You will lead AI assisted features in workflows, manage long running AI tasks with retries, determinism, versioning and auditing. Onsite AU-NSW-Sydney, Full Time, No travel. To apply, tailor your resume to highlight AWS, APIs, microservices, CI/CD IaC, and AI projects, provide concrete AI workflow examples, and include a brief note on how you would contribute to their AI enabled platform.
Full Stack Developer - (CREQ244790)
Description
Experience - 10+ years for Staff Engineer (Lead) and 6+ years for Senior Software Engineer
Proficient in the following AWS services with hands on experience: EC2, Lambda, DDB and S3
Exposure to AWS services like Kinesis, Firehose, Cloud watch, Aurora, Step Functions, CDK, Cloud Formation
Proficient in at least one of the 2 tech stacks: TypeScript/Node.js/Next.js - Primary and Preferable, or C#/.Net
Experience designing APIs and service contracts
Familiarity with event-driven architectures
Hands-on experience with CI/CD and IaC pipelines
Distributed systems and Microservices
Design and integrate AI-assisted features into workflow and platform services, such as:
Workflow and rules inference from structured and semi-structured inputs
Intelligent routing, classification, and recommendations within workflows
AI-assisted validation, schema evolution, and decision support
Partner with platform and security teams to ensure safe, explainable, and compliant AI usage.
Calling LLMs or AI services from long-running workflows
Handling retries, fallbacks, and determinism in AI-driven steps
Versioning and auditing AI-influenced decisions
Evaluate build vs buy options for AI services (managed cloud services vs internal capabilities