Full Stack Development Lead
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Role details
Tech stack
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Job description
Ruby on Rails Nginix Data Engineering - API integrations, Data pipelines ETL etc. .Net, C# Lead material, Absolute spot-on Client/Stakeholder management
We are looking for a Full Stack Development Lead who can provide hands-on technical leadership for AI-led software delivery while continuing to contribute to production-grade microservices development using .NET and C#. This role is expected to guide engineering teams, define delivery guardrails, review architecture and code quality, and ensure responsible use of AI coding assistants across the SDLC., * Lead the design, development, testing, and delivery of scalable microservices using .NET, C#, APIs, and database-backed services.
- Provide technical direction to developers on service boundaries, API contracts, resilience patterns, integration design, and containerized deployment approaches.
- Drive AI-led SDLC adoption across development, test generation, refactoring, debugging, documentation, code review, and onboarding workflows.
- Establish engineering guardrails for AI-generated code, including code review standards, test coverage, security checks, maintainability expectations, and responsible usage practices.
- Mentor developers on prompt engineering, AI-assisted development, critical review of generated code, and productivity-focused engineering practices.
- Partner with product, business, architecture, and delivery stakeholders to convert business outcomes into high-quality technical delivery plans.
- Own technical risk identification, dependency management, delivery quality, and engineering productivity improvements for the development track.
Requirements
Database Extract Transform and Load (ETL), Data Management, Application Programming Interface (API), Microsoft C# (C Sharp), Microsoft .NET, Microservices, Software Engineering, Technical Leadership, Software Development Lifecycle (SDLC), Artificial Intelligence (AI), * Strong hands-on expertise in .NET, C#, microservices development, APIs, and production-grade backend engineering.
- Demonstrated experience leading development teams or workstreams in complex application delivery programs.
- Deep understanding of microservices architecture, service decomposition, API design, resilience, observability, and deployment patterns.
- Strong database fundamentals including schema design, query optimization, transactions, SQL, and data access performance tuning.
- Practical experience using AI coding assistants such as Claude, GitHub Copilot, or similar tools in real delivery workflows.
- Ability to define AI-assisted engineering standards and critically review AI-generated code for correctness, security, maintainability, and performance.
- Experience with SDET practices, automated testing, quality engineering, secure coding, and CI/CD-driven delivery.
- Strong communication, mentoring, stakeholder management, and technical decision-making skills.
Additional Development Lead Skills
- Ability to own technical solutioning, estimation, design reviews, and delivery planning for the development track.
- Experience conducting code reviews, architecture walkthroughs, design validation, and technical quality governance.
- Capability to coach teams on AI-first development practices while ensuring accountability for human review and engineering judgment.
- Experience defining reusable engineering patterns, reference implementations, development standards, and onboarding playbooks.
- Ability to collaborate with architects and delivery leaders on modernization, cloud readiness, scalability, security, and operational reliability.
- Strong problem-solving skills with the ability to unblock teams, resolve technical dependencies, and make pragmatic delivery decisions.
Preferred Skills
- Exposure to Ruby on Rails for hybrid service maintenance or modernization scenarios.
- Experience with cloud-native engineering, containerization, observability, DevSecOps, and secure deployment pipelines.
- Experience improving engineering productivity through reusable accelerators, automation, AI-enabled development workflows, and quality dashboards.
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