Technical Lead Manager

Responsibilities

• Own the technical strategy and execution for the AI Frontend team, driving projects from initial idea formulation and detailed system design through high-quality implementation and successful deployment.
• Provide deep technical oversight by actively participating in design reviews, architecture discussions, and complex frontend system implementations — ensuring scalability, reliability, and exceptional user experience.
• Serve as a key technical contributor and subject matter expert in AI/ML-powered frontend development, setting the bar for engineering excellence and coding best practices across the team.
• Collaborate closely with product managers and UX/UI designers to translate user needs and business objectives into clear technical roadmaps and production-ready solutions.
• Mentor and coach engineers on complex technical challenges and career development; grow a strong, diverse team through proactive and deliberate hiring.
• Define team plans and deliverables while remaining accountable for the frontend platform's availability, performance, and maintainability across the full AI application lifecycle.
• Lead the improvement of engineering processes, tooling, and standards — with a focus on velocity, code quality, and developer experience.
• Partner effectively with backend, platform, and cross-functional teams to ensure smooth integration and influence the direction of the broader AI applications platform.
• Champion the use of AI coding assistants (such as Claude Code, Cursor, Codex, or similar tools) as a core part of the team's development workflow, modeling and scaling AI-native engineering practices.

Requirements

• 9+ years of experience designing and building large-scale, user-facing systems in production.
• 3+ years of experience managing and leading teams delivering mission-critical, high-concurrency, low-latency user interfaces.
• Deep hands-on proficiency in JavaScript/TypeScript and the React ecosystem; ability to drill into complex frontend architecture and implementation on a routine basis.
• Proficiency in at least one additional language such as Python, Go, or Java.
• Strong understanding of software engineering principles including design patterns, data structures, algorithms, and system design.
• Demonstrated ability to translate product requirements into technical specifications and lead engineering execution from concept to launch.
• Excellent collaboration and communication skills across engineering, product, and design stakeholders.
• BS/MS/PhD in Computer Science, Engineering, or a related field, or equivalent experience.

Nice-to-Haves

• Experience building or shipping LLM-powered applications (through prior work, open source, or personal projects).
• Active use of AI coding assistants in your daily workflow — you treat AI as a high-trust collaborator, not just an autocomplete tool.
• Experience with cloud environments such as AWS, Azure, or GCP.
• Prior experience working on data analytics, BI, or conversational AI products for enterprise customers.
• Familiarity with backend services and APIs that power AI/ML inference or data retrieval at scale.