Key Responsibilities :

Technical Leadership :

- Own the system architecture, technical strategy, and roadmap for one or more products.

- Lead architecture reviews, technology evaluations, and key technical decisions.

- Drive adoption of AI/LLM and Agentic AI capabilities across products and engineering workflows.

- Review complex designs, code, and pull requests to ensure high engineering standards.

- Drive improvements in scalability, performance, reliability, security, and system resilience.

- Lead production incident reviews, root-cause analysis, and long-term corrective actions.

- Establish and promote engineering best practices, design standards, and technical excellence.

People Leadership :

- Lead, mentor, and manage a high-performing team of 6 - 12 engineers.

- Conduct regular one-on-ones, performance reviews, career planning, and development discussions.

- Hire, coach, develop, and retain strong engineering talent.

- Foster a culture of ownership, collaboration, innovation, accountability, and continuous improvement.

- Provide technical guidance and mentorship to engineers while encouraging independent problem-solving.

Delivery Leadership :

- Own product roadmap execution, release readiness, and engineering delivery.

- Drive sprint planning, estimation, prioritization, and capacity planning.

- Identify and proactively manage technical risks, dependencies, and delivery challenges.

- Partner closely with Product, QA, DevOps, and other stakeholders to ensure predictable and high-quality delivery.

- Communicate engineering progress, risks, and priorities effectively to senior leadership and business stakeholders.

- Balance short-term delivery requirements with long-term architectural and technical investments.

Required Skills & Qualifications :

- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

- 15+ years of experience in software engineering, with significant experience in technical leadership and architecture.

- Proven experience designing and building large-scale, cloud-native, distributed systems.

- Strong expertise in software architecture, system design, scalability, reliability, performance, and security.

- Hands-on experience with AI/ML, LLMs, Generative AI, and/or Agentic AI and their application in production systems.

- Strong experience with modern cloud platforms, microservices, APIs, containers, and DevOps practices.

- Excellent understanding of software development lifecycle, engineering methodologies, and CI/CD practices.

- Proven experience leading and mentoring engineering teams of 6-12+ members.

- Strong experience in architecture reviews, technical decision-making, code reviews, and engineering standards.

- Demonstrated ability to manage product roadmaps, delivery risks, dependencies, and stakeholder expectations.

- Excellent communication, leadership, problem-solving, and decision-making skills.

- Strong ability to balance technical excellence, business priorities, and delivery commitments.