Principal Engineer & AI-Native Engineering Lead

Overview

Principal Engineer & Technical Lead to establish and lead a small, highly autonomous engineering team combining experienced technical leadership, talented developers, and AI coding agents such as Claude Code and OpenAI Codex. This is a hands-on role, not a traditional engineering management position.

What you'll do

• Own the technical architecture, design decisions, and implementation strategy for the team's applications, services, and systems.
• Translate business objectives and product requirements into pragmatic, maintainable technical solutions.
• Make sound trade-offs between delivery speed, reliability, security, scalability, and long-term maintainability.
• Establish lightweight engineering standards, architectural patterns, coding conventions, and documentation practices.
• Identify opportunities to simplify systems, eliminate unnecessary complexity, and accelerate delivery.
• Ensure the team builds software that can be understood, tested, operated, and evolved by engineers beyond its original authors.
• Make AI coding agents a first-class part of the development lifecycle, using tools such as Claude Code, OpenAI Codex, and other appropriate AI engineering tools.
• Develop effective workflows for AI-assisted requirements analysis, code generation, test creation, debugging, refactoring, code review, and documentation.
• Decompose work into clear, bounded tasks that AI agents can execute independently, in parallel, and with measurable results.
• Establish project context, repository instructions, reusable prompts, agent skills, automated checks, and other mechanisms that improve the consistency of AI-generated work.
• Evaluate AI-generated code critically, recognizing when to accept, modify, or reject its output.
• Continuously improve the team's engineering workflow based on actual delivery results rather than AI usage or code-generation volume.
• Take responsibility for delivering production-ready capabilities from problem definition through deployment and operational support.
• Collaborate with business stakeholders, product owners, users, and other engineering teams to clarify requirements and prioritize work.
• Break larger initiatives into small, independently testable increments that can be delivered frequently.
• Identify and resolve technical blockers without introducing unnecessary meetings, dependencies, or handoffs.
• Establish appropriate observability, deployment automation, rollback procedures, and operational safeguards.
• Monitor production outcomes and use feedback to improve the product and engineering process.
• Define a practical quality strategy covering automated testing, code review, integration testing, and production validation.
• Ensure AI-generated changes are verified through appropriate tests, static analysis, security checks, and human review.
• Establish guardrails for AI access to source code, credentials, production systems, customer data, and other sensitive resources.
• Prevent shortcuts that create unacceptable security, reliability, compliance, or maintainability risks.
• Make quality controls increasingly automated so that a small team can move quickly without relying on manual inspection for every routine check.
• Lead by example through hands-on engineering, thoughtful technical decisions, and disciplined execution.
• Mentor two supporting engineers through pairing, code reviews, design discussions, and progressively more challenging assignments.
• Build a culture of ownership, experimentation, direct communication, accountability, and continuous learning.
• Help engineers develop the judgment to direct AI agents, validate their work, and solve problems independently.
• Avoid becoming a bottleneck by delegating meaningful ownership and creating reusable patterns and automated guardrails.
• Share successful AI engineering practices with the broader engineering organization.

What you'll need

• Significant professional software engineering experience, typically 8+ years, with demonstrated technical leadership appropriate to a Principal or Staff+ engineer.
• Strong software design and architecture skills, with the ability to balance simplicity, delivery speed, maintainability, and operational needs.
• Demonstrated experience delivering and operating production software end to end.
• Strong programming skills in at least one of our primary technology stacks, with the ability to work across application layers when needed.
• Deep understanding of testing strategies, CI/CD, version control, observability, application security, and production troubleshooting.
• Practical experience using AI coding agents such as Claude Code, OpenAI Codex, or comparable tools in real engineering workflows.
• Ability to break ambiguous business problems into well-defined technical tasks and independently drive them to completion.
• Excellent technical communication, problem-solving, mentoring, and decision-making skills.
• A track record of taking ownership of outcomes rather than limiting responsibility to assigned implementation tasks.

Nice to have

• Experience building or leading small, autonomous, cross-functional engineering teams.
• Experience with agentic coding workflows, parallel AI task execution, repository-level instructions, and automated validation pipelines.
• Experience establishing internal developer platforms, reusable engineering templates, or AI-enabled development infrastructure.
• Experience in our relevant industry, domain, and technology stack.
• Experience improving delivery lead time, software quality, operational reliability, or engineering productivity through measurable changes.

Details

• Location: Home, India (remote).