Advisory Hub – Fullstack Tech Lead

Role: Fullstack Tech Lead

Job Summary
We are seeking a highly capable and hands-on Fullstack Tech Lead to provide both technical leadership and active development across the front-end and back-end domains. This role bridges the front-end and back-end teams, ensuring alignment, performance, and technical excellence across the stack. The Tech Lead will mentor 2–4 developers, lead code reviews, and partner closely with product, UX, and DevOps teams to deliver enterprise-grade, GenAI-enabled solutions leveraging client's Solution Studio and Delivery Methodology (PDM). A core expectation is daily, practical use of AI assistants (e.g., GitHub Copilot, ChatGPT Enterprise, or equivalent) across the SDLC—coding, testing/QA, operations, and documentation. The Tech Lead models responsible AI usage, contributes and refines team "AI recipes," and demonstrates sound judgment in evaluating when generated code is "good" vs. "bad," including handling edge cases, security, performance, and maintainability concerns.

Key Responsibilities
Technical Leadership & Architecture

• Define and guide the overall system architecture, ensuring scalable and maintainable fullstack solutions.
• Oversee integration between front-ends and back-ends.
• Implement best practices in state management, caching, and data modeling for optimal performance.
• Enforce high coding standards, reusable design patterns, and automated testing coverage.

Hands-On Development

• Contribute directly to both client-side and server-side codebases.
• Design and develop secure, efficient APIs (REST and GraphQL) to support feature-rich front-end experiences.
• Implement responsive, accessible, and high-performance UIs with React and TypeScript.
• Optimize build pipelines, deployments, and service interactions within Azure environments.

AI-Enabled Engineering & Quality

• Use AI assistants daily for tasks such as scaffold generation, test creation, refactor suggestions, docstrings, and runbook drafts—and teach the team when to accept, modify, or discard outputs.
• Recipes: Contribute to and evolve team AI recipes (prompt patterns, guardrails, review checklists, fallback steps) tuned to project use cases.
• Quality gate: Validate AI-generated code against acceptance criteria, security best practices, performance budgets, and maintainability (readability, coupling, testability).

Team Enablement & Mentorship

• Mentor engineers on system design, code quality, and effective AI usage (prompting techniques, verification habits, review heuristics).
• Review pull requests, guide refactoring efforts, and ensure delivery consistency.
• Promote knowledge sharing, pair programming, and continuous improvement within the team.

Agile Collaboration & Delivery

• Participate in Agile ceremonies and drive sprint-level technical planning.
• Collaborate with Product Owners, UX, and DevOps to align priorities and remove delivery blockers.
• Ensure technical feasibility of UI/UX designs and platform features.
• Contribute to CI/CD optimization and DevOps integration practices.

Continuous Improvement & Innovation

• Leverage GenAI tools for documentation, code generation, and testing acceleration.
• Evaluate emerging technologies and frameworks to improve developer productivity and platform scalability.
• Champion performance profiling, observability, and automation best practices.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 5-8+ years of professional experience in fullstack engineering roles.
• Proven expertise in React, , , and NestJS.
• Solid understanding of PostgreSQL or MongoDB, and API performance tuning.
• Experience with Azure services (Service Bus, Event Hub, Functions) and distributed systems.
• Familiarity with CI/CD pipelines (GitHub workflows, trunk-based development).
• AI assistants: Demonstrated daily use of Copilot and at least one other AI tool across coding, QA, operations, and documentation; ability to articulate where in the SDLC AI adds value, provide specific examples, and explain issues encountered and mitigations.
• Code judgment: Clear ability to discern good vs. bad AI-generated code—validate correctness, security, performance, readability, testability, and long-term maintainability.
• Excellent communication, leadership, and mentoring skills.
• Strong background in Agile delivery and cross-functional collaboration.

Must Have:
React, , , NestJS, TypeScript, REST & GraphQL APIs, Azure (Service Bus, Event Hub, Functions), PostgreSQL or MongoDB, CI/CD pipelines, performance optimization, hands-on AI assistant usage (Copilot or other) across coding/QA/ops, ability to evaluate AI-generated code quality

Nice to Have:
Microfrontends, Nx monorepo, design system contributions, test automation, observability (DataDog), serverless architecture, experience codifying team AI recipes and measuring AI-driven productivity/quality gains