Lead Software Engineer

Role Overview and Responsibilities
Dhruva Space is seeking an experienced Tech Lead - Software Engineer to lead a pod of engineers building software using AI coding agents. The role will own end-to-end delivery, engineering quality, AI-agent governance, team development, and technical execution while working closely with architecture and product leadership.
Key responsibilities include but are not limited to:
Own end-to-end delivery of software products using AI coding agents.
Establish and enforce standards for code review, testing, security, and AI-agent governance.
Lead, mentor, and manage engineers across software, ML/agent systems, and QA disciplines.
Ensure AI-generated code meets required standards for quality, security, scalability, and production readiness.
Partner with architecture leadership on key technical and architecture decisions.
Collaborate with product leadership on roadmap feasibility, priorities, and delivery sequencing.
Own team hiring, onboarding, performance management, and capability development.
Drive engineering planning, execution, and continuous improvement across the team.
Identify and manage technical, delivery, and production risks.
Monitor engineering progress and communicate delivery status, risks, and dependencies to senior leadership.
Establish effective engineering practices for AI-assisted development and production delivery.
Support 0-to-1 product development and help scale engineering practices as the organization grows.
Candidate Requirements:
Bachelor’s or Master’s degree in Computer Science, Engineering, IT, or a related field.
8–12 years of experience in software engineering, technical leadership, or engineering management.
Hands-on experience working with AI coding agents such as Claude Code, Cursor, or GitHub Copilot.
Strong code-review skills with the ability to identify correctness, security, and architectural issues in AI-generated code.
Proven experience managing, mentoring, and developing engineering teams.
Strong technical breadth across full-stack development and cloud infrastructure.
Working knowledge of AI agent orchestration, tool use, prompting, and multi-agent workflows.
Ability to make sound technical decisions and manage ambiguity in fast-paced environments.
Experience with LangGraph, CrewAI, MCP, or similar agent orchestration frameworks is preferred.

Work arrangement
No