Technical Leadership: Lead, mentor, and inspire a team of engineers, fostering a culture of ownership, continuous learning, growth, collaboration, and engineering excellence.
Technical Strategy: Define and execute the technical strategy and roadmap for your team, aligning it with business objectives, product priorities, customer commitments, and organizational goals.
Code Review: Conduct thorough code reviews to maintain code quality, improve maintainability, identify refactoring opportunities, and provide constructive feedback to team members, including on AI-generated code.
AI-Assisted Engineering: Drive adoption of AI-assisted coding and productivity tools such as Cursor, GitHub Copilot, ChatGPT, Claude, or similar tools for development, testing, debugging, documentation, codebase exploration, and refactoring.
LLM Awareness: Bring practical knowledge of LLMs, prompt engineering, RAG, AI agents, vector stores, model evaluation, and LLM observability, and guide teams in applying these concepts responsibly in product and engineering workflows.
Problem Solving: Troubleshoot and resolve complex technical issues, identify root causes, and implement effective long-term solutions across microservices, distributed systems, data platforms, and production environments.
Collaboration: Collaborate closely with product managers, designers, architects, DevOps, security, and other stakeholders to ensure alignment between technical solutions, product outcomes, customer needs, and business objectives.
Project Management: Lead the planning, execution, and successful delivery of features, ensuring they are completed on time, within scope, and to the highest quality standards.
Technical Excellence: Drive innovation and adoption of best practices in development, architecture, testing, observability, security, performance, cost optimization, and modern AI-native engineering practices.
Architectural Guidance: Be a thoughtful technical voice and support your team in making diligent architectural decisions across APIs, microservices, event-driven systems, cloud infrastructure, data stores, and AI-enabled capabilities.
Production Ownership: Ensure your team owns production quality through observability, incident management, RCA, bug hygiene, performance tracking, SLOs, and continuous reliability improvements.
Performance Management: Conduct regular performance evaluations, provide feedback, support professional growth, and coach engineers on technical depth, ownership, communication, and execution.
