Sr. Full Stack Developer

Datascan is a technology company whose mission is to help businesses make better inventory decisions one scan at a time. Through the provision of configurable software, fit-for-purpose scanning hardware, and access to real-time data, Datascan is the cost effective, high value option for retailers looking to take advantage of the accuracy, efficiency, and flexibility of our industry-leading inventory solutions.

We operate using several key drivers for success which include
-Establishing lasting, collaborative client relationships that consistently exceed expectations,Continually striving for excellence through innovation, technical expertise, industry knowledge and a relentless commitment to client care,Being easy to do business with, in all that we do,Attracting, developing, and retaining passionate, talented people in a culture of empowerment that inspires, challenges, and recognizes the contribution of every member of the Datascan team.

Backed by private equity and with over 50 years of experience serving retailers, Datascan is the global leader in providing technology-led inventory counting solutions to world class retailers in over 42 countries.

Position Summary 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.

Duties & Responsibilities Deliver business-ready software solutions

Own technical analysis for complex features, workflows, integrations, and cross-system capabilities.

Partner with product and business stakeholders to clarify the business outcome, user workflow, acceptance criteria, and operational impact.

Translate ambiguous business problems into solution options, technical designs, delivery plans, and measurable success criteria.

Advise on technical tradeoffs, risk, sequencing, dependencies, and long-term maintainability.

Design, develop, and maintain complex web applications, APIs, integrations, data models, services, and platform capabilities.

Ensure solutions are scalable, secure, performant, observable, maintainable, and aligned to architecture and engineering standards.

Lead troubleshooting and root cause analysis for complex defects, production issues, and performance bottlenecks.

Conduct code reviews and guide developers on technical quality, maintainability, and effective AI-assisted development practices.

Design and execute AI-assisted development workflows for complex coding, refactoring, testing, analysis, documentation, and troubleshooting activities.

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

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 &…