Responsibilities- Manage squad performance, set goals, and track progress while providing direct mentorship to foster a culture of continuous growth.
- Lead and develop an engineering team focused on building foundational AI and ML capabilities that support the broader AI organization.
- Act as a technical leader, translating AI and ML requirements into scalable technical architectures and platform solutions.
- Partner closely with Product and Engineering leadership to define, prioritize, and execute the technical roadmap for AI platform and infrastructure capabilities.
- Drive the development of foundational capabilities across areas such as ML pipelines, AI infrastructure, compute, model evaluation, and platform scalability.
- Support high-level technical decisions and architectural guidance, ensuring the team delivers performant, reliable, scalable, and optimized solutions.
- Work closely with AI and engineering teams to understand their infrastructure needs and build reusable foundational capabilities that enable the development and deployment of AI systems.
- Lead people management initiatives, including 1:1s, career development, hiring, and maintaining high motivation levels within the squad.
- Optimize development processes and identify opportunities to improve engineering productivity through AI-assisted development tools and practices.
- Generate exemplary technical documentation to establish strong foundations for the squad's long-term success.
- Anticipate future AI platform, infrastructure, compute, and architecture requirements as the organization scales.
Requirements- Proven experience in team management, ideally with 3+ years leading direct reports, with a strong track record of leading and developing engineering teams in a fast-paced technology environment.
- 10+ years of experience in software engineering, machine learning, AI infrastructure, or related technical domains.
- Strong experience building or leading ML pipelines, AI/ML platforms, foundational AI systems, or related infrastructure.
- Experience working with areas such as compute infrastructure, model evaluation, scalable AI platforms, or machine learning systems.
- Strong delivery-oriented mindset, with experience supporting stakeholders and coordinating teams to achieve tangible technical and business results.
- Ability to operate at a high technical level, focusing on system design, architecture, and technical problem-solving rather than solely hands-on coding.
- Experience working closely with ML engineers, AI engineers, data scientists, or other technical teams.
- Excellent communication and interpersonal skills to collaborate effectively with Product, Engineering, and other cross-functional stakeholders.
- Ability to inspire and motivate a team, taking full ownership of developers' growth and career development.
- Bias for action and ability to operate effectively in a fast-moving environment.
- Capacity to anticipate future AI infrastructure, platform, and architecture requirements.
Our tech stackWe are technology agnostic and value candidates with diverse backgrounds. While familiarity
with the following is helpful, your willingness to learn and adapt is paramount:
- AI: Google ADK, langfuse, open AI api, Gemini Apis, etc.
- Back-end: Python, Flask/Fast, REST APIs, Redis, SQL
- Cloud: Google Cloud services (Firestore, Cloud Storage, Pub/Sub, Google Artifact Registry, Cloud Run, BigQuery, Cloud Composer, etc.)
- Infrastructure: Kubernetes, Terraform, NewRelic
What We Offer- Base: $232,000 - $280,000. Flexible depending on location and interview performance
- Initial stock options grant
- Annual performance bonus
- Health, dental, and vision plans
- 401(k) with an employer's match
- Continuous learning opportunities
- Unlimited PTO
- Paid parental leave
- Empowering opportunities for growth in a dynamic entrepreneurial environment
CompensationThe base pay range for this role is $232,000 - $280,000 per year.
