Job Description
Job Description
This role is accountable for owning complex software solutions from business problem definition through technical design, AI-enabled execution, validation, and production support. Responsible for translating business requirements into secure, scalable, high-quality software solutions through the design, development, testing, deployment, support, and continuous improvement of front-end and back-end applications while collaborating across teams to deliver business outcomes. The Sr. Full Stack Developer applies advanced full stack engineering judgment and responsible agentic AI practices to deliver high-impact SaaS capabilities with speed, quality, and maintainability. This role partners with product owners, architects, technical leads, QA, business stakeholders, and other developers to resolve ambiguity, shape implementation strategy, establish reusable development patterns, and mentor team members in effective use software development tools and methodologies.
Ensure quality, secure, and scalable systems
Ensure quality, secure, and scalable systems
Establish validation approaches for code, documentation, test cases, and technical recommendations.
Define automated test strategies, evaluation criteria, and quality gates for complex or high-risk work.
Define and deliver non-functional requirements.
Create clear technical documentation, implementation notes, prompt documentation, and operational handoff materials.
Identify and mitigate risks related to AI-generated output, including hallucinations, insecure code, data leakage, hidden assumptions, and maintainability issues.
Ensure development practices comply with company standards for security, privacy, intellectual property, access control, data protection, and customer trust.
Contribute to continuous improvement & engineering practices
Participate in code reviews and incorporate feedback from others.
Mentor developers on full stack development, business problem solving, prompt design, AI tool usage, and validation practices.
Drive continuous improvement of engineering standards, AI-enabled workflows, testing practices, documentation, and delivery methods.
Partner with technical leadership to evaluate emerging tools, frameworks, and AI development practices for practical team adoption.
Reduce friction, waste, and inefficiencies within the software delivery lifecycle.
Continuously improve skills in software engineering, prompt engineering, AI-assisted development, and Datascan domain knowledge achieving status as subject matter expert.
Resolve production issues and technical debt
Investigate and resolve application defects and production issues with high complexity and urgency.
Perform root cause analysis and implement corrective actions.
Support ongoing application reliability and operational performance.
Improve long-term platform maintainability through continuous modernization, refactoring, and architectural improvements
