Back
Tier-1 employer and metro location, balanced by seniority and AI specialization limiting generalist applicants.
Core full-stack skills are transferable, but AI, regulated delivery, and product ownership needs increase domain specificity moderately.
Explicit 8-13 years and mandatory full-stack plus AI integration skills and regulated-delivery experience create strict filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own end-to-end delivery of a small full-stack AI product or significant technical workstream from problem framing to adoption and measurable business outcomes.
Lead architecture, implementation, launch, stabilization, and support transition spanning frontend, backend, APIs, AI integrations (ML, Generative AI, RAG, agents), security, and user experience.
Manage engineering decisions, sprint/releases planning, governance, testing, CI/CD, observability, incident response, and cross-functional coordination including mentoring engineers.
Bachelor’s or Master’s degree in Computer Science, IT or related field.
8 to 13 years of professional experience in full-stack software development and AI-enabled systems.
Proven full ownership of at least one production full-stack application or AI-enabled system delivering measurable outcomes.
Strong hands-on skills in JavaScript/TypeScript and at least one backend language (Python, Java, C#, or Node.js) plus SQL.
Experienced in architecting and delivering AI-enabled, distributed, secure, and scalable full-stack applications integrating ML, Generative AI, RAG, and automation.
Skilled in product and technical leadership balancing hands-on engineering with cross-functional collaboration and measurable business value delivery.
Familiar with regulated environments (e.g. GxP), DevSecOps, cloud platforms (AWS, Kubernetes), and advanced AI tooling relevant to enterprise AI product lifecycle.