Location: Anywhere in Country
The opportunityYou'll help build and modernize digital products and applications using an AI-first delivery approach. In this role, you'll pair traditional engineering fundamentals with AI tooling to accelerate design, coding, testing, documentation and release-while maintaining high quality, security and Responsible AI standards. You'll work in cross-functional squads (product, design, engineering, QA, DevOps) delivering outcomes for clients across industries.
Your key responsibilities
AI-native delivery (build)
- Use AI coding assistants to generate, refactor and modernize code while applying secure-by-design practices and peer review discipline.
- Translate user stories and acceptance criteria into working software with strong engineering fundamentals (readability, modularity, performance).
- Create and maintain reusable components, templates and accelerators that improve team velocity and consistency.
- Apply prompt patterns and structured context (docs, schemas, examples) to improve AI outputs and reduce rework.
Quality engineering (test)- Use AI tools to draft unit/integration tests, contract tests and test data; validate coverage and edge cases with engineering judgment.
- Implement automated QA in CI/CD (linting, SAST/DAST, dependency scanning, performance checks, test gates).
- Support exploratory testing and defect triage; drive root-cause fixes rather than symptomatic patches.
- Produce clear technical documentation and runbooks (including AI-assisted documentation) to support supportability and knowledge transfer.
DevSecOps and observability (run)- Contribute to pipelines, environments and release automation; ensure builds are repeatable and auditable.
- Instrument services for logs/metrics/traces; help define SLOs/SLIs and error budgets for critical paths.
- Assist with incident response by using AI tools to summarize telemetry, propose hypotheses and accelerate remediation-under human oversight.
Client and team collaboration- Collaborate with product owners and designers to turn intent into implementable technical plans.
- Communicate progress, risks and tradeoffs; contribute to estimation and sprint planning.
- Mentor junior teammates on AI-augmented engineering practices (prompting, validation, secure use of tools).
Skills and attributes for success- Strong foundation in software engineering: data structures, APIs, version control, code review and debugging.
- Hands-on experience building web and/or cloud applications (front-end, back-end or full-stack).
- Practical knowledge of automated testing and CI/CD; ability to improve quality through automation.
- Comfort using AI tools (coding assistants, test generation, documentation) with disciplined validation and security awareness.
- Curiosity, learning agility and the ability to explain technical concepts to non-technical stakeholders.
Ideally, you'll also have- Experience with cloud-native development (Azure/AWS/GCP), containers and infrastructure-as-code concepts.
- Familiarity with modern front-end frameworks and/or API design patterns (REST/GraphQL/event-driven).
- Exposure to Responsible AI concepts (privacy, data handling, bias, model risk) and secure coding standards.
- Experience building with or integrating GenAI capabilities (prompting, RAG patterns, embeddings, evals) is a plus.
Qualifications- Bachelor's degree in Computer Science, Engineering or a related discipline (or equivalent experience).
- Typically 4+ years of professional software development experience (consulting or product teams).
- Experience delivering in Agile teams and collaborating across product, design and QA.
What we look forWe're looking for people who are builders and problem solvers-team-oriented, client-focused and committed to quality. You bring a 'learn fast, ship responsibly' mindset, combine AI acceleration with sound engineering judgment, and help teams adopt new ways of working without compromising trust.
What we offer you- The ability to work on transformative digital product builds with global clients.
- A collaborative, inclusive culture with access to modern engineering platforms and AI-enabled delivery tools.
- Career-long learning, certifications and coaching to grow both technical depth and consulting impact.
- Flexible work options (subject to engagement needs).
Responsible use of AI tools (non-negotiable)- Follow EY and client policies for data handling; do not enter confidential client data into non-approved tools.
- Validate AI-generated outputs through testing, review and security checks; humans remain accountable for final deliverables.
- Use AI to accelerate work-not to bypass controls, quality gates or professional judgment.
Are you ready to shape your future with confidence? Apply today. EY accepts applications for this position on an on-going basis.
For those living in California, please click here for additional information.
EY focuses on high-ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.
