
501 - 1000 employees
Founded 2015
☁️ SaaS
👥 HR Tech
🏢 Enterprise
SaaS • HR Tech • Enterprise
Lattice is a people management platform designed to help organizations improve employee engagement, performance, and development. It offers tools for performance reviews, goal setting, employee feedback, and analytics to help HR teams and managers foster a high-performance culture. Lattice integrates with various HRIS systems and aims to streamline HR operations by centralizing data and automating workflows. The platform supports strategic HR teams in managing employee information, driving performance, capturing team sentiment, and providing insights, ensuring that the company can build operational excellence and meaningful work experiences for employees.
🔥 22 hours ago
🇨🇦 Canada – Remote
💵 $146.3k - $195k / year
⏰ Full Time
🟡 Mid-level
🟠 Senior
👮♀️ Software Engineering Manager
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501 - 1000 employees
Founded 2015
☁️ SaaS
👥 HR Tech
🏢 Enterprise
SaaS • HR Tech • Enterprise
Lattice is a people management platform designed to help organizations improve employee engagement, performance, and development. It offers tools for performance reviews, goal setting, employee feedback, and analytics to help HR teams and managers foster a high-performance culture. Lattice integrates with various HRIS systems and aims to streamline HR operations by centralizing data and automating workflows. The platform supports strategic HR teams in managing employee information, driving performance, capturing team sentiment, and providing insights, ensuring that the company can build operational excellence and meaningful work experiences for employees.
• Lead, coach, and grow a high-performing team of AI and software engineers, developing them into strong technical leaders while fostering a culture of ownership, technical excellence, experimentation, and continuous learning. • Own the execution and delivery of the AI Platform roadmap, balancing near-term product impact with long-term platform investments. • Partner closely with Product, Applied AI, Data Science, and engineering leaders to define how AI quality is measured, evaluated, and continuously improved across Lattice. • Lead the development of AI evaluation infrastructure, quality metrics, experimentation capabilities, observability, and developer tooling that enable every AI product team to confidently build, evaluate, and ship AI experiences. • Drive technical and organizational decisions that improve the scalability, reliability, and adoption of the AI Platform, empowering engineers to own architecture and technical solutions. • Build strong cross-functional partnerships and influence engineering strategy to establish AI evaluations as a foundational capability that accelerates AI development across Lattice.
• Experience leading and growing high-performing software engineering teams, with a track record of hiring, coaching, and developing engineers into strong technical leaders. • Strong technical background leading teams that build AI infrastructure, AI-powered products leveraging Large Language Models (LLMs) and/or AI agents, distributed systems, or developer platforms. You are a highly technical engineering leader who leads by example—contributing to architecture, design reviews, and code reviews, diving into implementation details when needed, and raising the technical bar across the team. • Experience building enterprise SaaS AI products where quality, trust, reliability, and scalability are critical to customer success. • Proven ability to lead complex cross-functional initiatives from strategy through execution, partnering effectively with Product, Applied AI, Data Science, and Engineering to deliver business impact. • Excellent communication and stakeholder management skills, with the ability to create clarity, align teams, and influence technical direction in fast-moving, ambiguous environments. • A strong product and platform mindset, balancing customer impact, engineering velocity, operational excellence, and long-term technical investments. • A leadership style grounded in curiosity, humility, ownership, and continuous learning, with a passion for building exceptional engineering teams and delivering high-quality AI products. • Nice to Have: Experience building AI evaluation frameworks, experimentation platforms, or ML infrastructure. Knowledge of statistical experimentation, A/B model testing, offline evaluations, or model benchmarking. Familiarity with advanced AI optimization techniques such as Direct Preference Optimization (DPO), Reinforcement Learning from Human Feedback (RLHF), model fine-tuning, or preference learning. Experience building internal platforms and services adopted across multiple engineering teams.
• Medical insurance • Dental insurance • Life, AD&D, and Disability Insurance • Natural Disaster Support Program • Wellness Apps • Paid Parental Leave • Paid Time off inclusive of holidays and sick time • Working Remotely Stipend • One time WFH Office Set-Up Stipend • Retirement Plan • Financial Planning • Learning & Development Budget
Apply Now🔥 22 hours ago
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