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.