[Hiring] Lead Software Engineer @Lifeloop

Role Description

This is a high-level individual contributor engineering role. As the most senior individual contributor on the team, the Lead Software Engineer leads innovation and sets the technical standard for the entire engineering team. This person is deeply AI-native — not just using AI tooling, but actively championing and evolving AI-driven development workflows across the engineering organization.

LifeLoop is an AI-native engineering organization. All roles are expected to be proficient with the latest AI development tooling and workflows, and to actively keep pace with rapid advancements in this space. The engineering team is organized into focused squads operating on a Kanban model, with a culture of spec-driven development, pragmatic execution, and continuous improvement.

What can you expect the role to look like:

• Lead development of the most complex products and features on the LifeLoop platform
• Identify and drive adoption of emerging AI tools and workflows that improve how the team builds software
• Serve as a technical coach to both engineering leads and junior engineers — helping the team level up technically and in their use of AI-assisted development
• Contribute to the engineering playbook and continuously evolve how the team works
• Operate with a pragmatic coaching style — hands-on, not just advisory
• Set and uphold engineering quality standards across the codebase
• Collaborate with product and leadership to shape the technical direction of the platform
• Drive spec-driven development practices and ensure technical specifications are clear, complete, and actionable

AI Expectations

This role is expected to be a visible champion of AI-native development. Proficiency with tools like Claude Code, and similar AI coding assistants is required. Willingness to experiment with new AI tooling, document learnings, and raise the entire team’s capabilities is essential. The Lead Software Engineer should be the person the team looks to for guidance on how to best leverage AI in their day-to-day workflows.

Qualifications

• Deep expertise across modern full-stack environments, including MERN, Java Spring Boot, cloud platforms such as AWS and/or Azure, and distributed systems.
• Proven track record of leading complex technical initiatives from design through delivery.
• Advanced proficiency in coding, unit testing, and technical design at scale — code should be trusted to scale, with known tipping points at time of authorship.
• Expert-level functional and technical design skills — ability to define technical specifications for work of high complexity and lead the architectural direction of the most complex strategic initiatives.
• Strong ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders.
• Demonstrated leadership in coaching and mentoring engineering teams without direct management authority.
• Experience pioneering new engineering standards based on modern best practices and communicating them to the broader team.
• Ability to lead change and champion new ways of working, including AI-driven development practices.
• Results-oriented mindset — leads across projects, lending expertise, guidance, and picking up work to ensure broad team objectives are met.
• Strong collaboration skills — able to form teams and organize efforts ensuring project assignments are equitable and efficient.
• Deep commitment to spec-driven development, pragmatic execution, and continuous improvement.