Senior Engineering Manager

Senior Engineering Manager

1. Role Description (Need of the Role):

This role requires a seasoned technical leader who has evolved from a hands-on developer to a manager, and who embraces AI as a fundamental accelerator of the software development lifecycle. The manager will lead a team of full-stack engineers, setting technical direction and ensuring high-velocity execution by leveraging the latest AI tools and agentic workflows.

Key responsibilities include:

• Champion an AI-First Development Culture: Lead the adoption, integration, and optimization of AI-driven coding tools (e.g., Claude Code and emerging autonomous agents) across the engineering team. Continuously evaluate and implement new AI tools to maximize productivity.
• Architectural Leadership & Problem Solving: Define the technical approach for complex projects spanning both frontend and backend systems. Provide architectural oversight and guidance to ensure solutions are scalable, maintainable, and efficient.
• Hands-On Technical Deep Dive: Act as the primary technical escalation point. If the team is blocked, you must be capable of diving into the codebase, debugging complex issues, and developing solutionseither directly or by effectively leveraging AI assistants for rapid prototyping and troubleshooting.
• Team Management and Mentorship: Manage and mentor a team of software engineers. Foster a culture of continuous learning, specifically guiding the team on effective prompt engineering and maximizing the utility of AI tools.
• Project Execution and Delivery: Oversee the end-to-end development lifecycle. Ensure timely delivery of high-quality software by optimizing workflows and removing bottlenecks.
• Cross-Functional Collaboration: Work closely with Product Managers and stakeholders to translate business requirements into technical execution plans.

Functional competencies (Must have skill):

Must Have:

• Strong Coding Foundations: High proficiency in at least one major backend language (e.g., Python, Java) AND familiarity with frontend frameworks (e.g., React).
• AI Tool Proficiency: Demonstrated experience using and integrating AI coding assistants (e.g., Claude Code, CLI agents) into daily workflows.
• System Design & Architecture: Proven ability to design scalable, distributed systems (understanding of microservices, databases, cloud architecture).
• Cloud Platforms: Experience with AWS, Azure, or GCP.
• DevOps Principles: Strong understanding of CI/CD pipelines, Git, and infrastructure as code.
• Technical Team Leadership: Prior experience managing or leading a software engineering team.

Good to Have:

• Agentic Workflows: Experience experimenting with or deploying autonomous coding agents (e.g., Jules, OpenAI Codex).
• Data Engineering Basics: Understanding of ETL processes and data warehousing.
• Vector Databases & RAG: Familiarity with concepts of embeddings and vector search.