Software Engineer - AI Assisted Development Project Summary We are looking for a Software Engineer to lead the adoption of AI-assisted coding practices across the organization. This role combines hands-on engineering, enablement, and governance—defining how AI is used in software development while actively supporting teams in building their first applications using AI-assisted workflows. You will act as both a coach and a quality gate, ensuring teams leverage AI effectively without compromising engineering standards. Main Responsibilities / Objectives AI-Assisted Development Practices * Define and standardize best practices for AI-assisted coding across teams. * Establish clear guidelines for when and how to use AI tools (generation, refactoring, testing, documentation). * Create reusable playbooks, patterns, and prompt libraries for effective AI usage. * Promote responsible usage with strong human-in-the-loop validation and traceability. Hands-On Enablement & App Development * Partner with teams to build their first applications using AI-assisted coding ("vibe coding"). * Review and guide early implementations to ensure quality, maintainability, and alignment with architecture standards. * Act as a technical coach, helping engineers translate AI-generated outputs into production-ready solutions. * Identify common pitfalls and turn them into reusable best practices and guardrails. Tooling & Integration * Evaluate and integrate AI coding tools (e.g., GitHub Copilot, Cursor IDE). * Embed AI into the development lifecycle (IDE, CI/CD, code reviews). * Build internal tooling or wrappers to: Standardize usage patterns, Enforce guardrails, Capture metrics and insights Engineering Quality & Governance * Define quality standards for AI-generated code (testing, security, performance). * Establish review processes adapted to AI-assisted development. * Ensure compliance with enterprise requirements (security, licensing, data privacy). * Prevent anti-patterns such as: Blindly trusting generated code, Inconsistent architectures, Duplication or technical debt at scale Developer Experience & Enablement * Train teams on effective AI-assisted workflows. * Create onboarding materials, demos, and real-world examples. * Scale knowledge across teams to ensure consistent adoption. Continuous Improvement * Run pilots and experiments with new AI tools and workflows. * Measure impact on productivity, quality, and delivery speed. * Continuously refine practices based on real usage and feedback. Expected Deliverables * A standardized framework for AI-assisted development. * Successfully delivered first applications built using AI-assisted workflows, with documented learnings. * Code reviews and guidance that elevate team output quality. * Internal tools, templates, and prompt libraries. * Training materials and onboarding sessions. * Measurable improvements in developer productivity and code quality. Required Skills * Experience: 5–10 years of experience in software engineering. * Proven experience building production-grade applications. * Hands-on experience using AI coding tools in real projects. * Experience mentoring or guiding other engineers. Software Engineering * Strong programming skills (TypeScript/JavaScript, Python, or similar). * Experience with modern architectures (APIs, distributed systems, frontend frameworks). * Strong foundation in testing, maintainability, and performance. AI-Assisted Development * Strong understanding of: Prompt engineering for code generation, Limitations and risks of LLM outputs, Validation and review patterns DevOps & Tooling * Familiarity with CI/CD, code quality tooling, and developer workflows. Governance & Security * Understanding of secure coding, compliance, and licensing considerations.