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

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.