Engineering Manager, AI
WFA Digital Insight
As the demand for AI specialists grows, with a 25% increase in job postings over the last year, experienced leaders are needed to spearhead these initiatives. Lattice stands out by focusing on building trustworthy and measurable AI solutions, a critical aspect in today's tech landscape. For candidates, having a strong technical background in AI infrastructure and experience in leading cross-functional teams are highly valued. Before applying, consider how your skills align with the growing need for AI quality assurance and the ability to drive technical decisions in a fast-paced environment.
Job Description
About the Role
The Engineering Manager for AI at Lattice plays a pivotal role in ensuring the company's AI solutions are not only cutting-edge but also trustworthy, measurable, and continuously improving. This is achieved through leading the AI Intelligence Quality (IQ) team, which is responsible for the AI Platform that enables every AI team at Lattice to measure quality, detect regressions, run experiments, and improve AI performance with confidence.
The role involves managing a high-performing team of AI and software engineers, fostering a culture of ownership, technical excellence, experimentation, and continuous learning. A key aspect of this position is balancing near-term product impact with long-term platform investments, ensuring that the AI Platform roadmap is executed and delivered effectively.
Given the critical nature of AI in product experiences, this role is central to shaping the quality of every AI experience delivered by Lattice. The successful candidate will have a strong technical background and experience in leading teams that build AI infrastructure, AI-powered products, distributed systems, or developer platforms.
What You Will Do
- Lead, coach, and grow a high-performing team of AI and software engineers, focusing on developing them into strong technical leaders.
- Own the execution and delivery of the AI Platform roadmap, balancing immediate product needs with long-term strategic investments.
- Partner closely with Product, Applied AI, Data Science, and other engineering leaders to define and implement how AI quality is measured, evaluated, and improved across Lattice.
- Lead the development of AI evaluation infrastructure, quality metrics, experimentation capabilities, observability, and developer tooling.
- Drive technical and organizational decisions to improve the scalability, reliability, and adoption of the AI Platform.
- Build and maintain strong cross-functional partnerships to influence engineering strategy and establish AI evaluations as a foundational capability.
- Collaborate with stakeholders to ensure alignment and support for AI quality initiatives.
- Stay updated on the latest advancements in AI technology and apply this knowledge to improve Lattice's AI solutions.
What We Are Looking For
- Experience leading and growing high-performing software engineering teams, with a proven track record of hiring, coaching, and developing engineers into technical leaders.
- Strong technical background in AI infrastructure, AI-powered products, distributed systems, or developer platforms.
- Experience in building enterprise SaaS AI products with a focus on quality, trust, reliability, and scalability.
- Proven ability to lead complex cross-functional initiatives from strategy through execution.
- Excellent communication and stakeholder management skills, with the ability to create clarity and align teams in fast-moving environments.
- A product and platform mindset, balancing customer impact, engineering velocity, operational excellence, and long-term technical investments.
- 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, etc.
Benefits and Perks
- Competitive compensation package, tailored to attract top talent in the AI field.
- Opportunities for professional growth and development in a cutting-edge technology environment.
- Flexible and remote work arrangements, supporting a healthy work-life balance.
- Access to the latest tools and technologies, ensuring engineers have what they need to excel.
- Comprehensive health and wellness programs, recognizing the importance of employee well-being.
- Generous PTO policy, encouraging time off to recharge and pursue personal interests.
- Remote stipend, acknowledging the importance of a comfortable and productive home workspace.
- Equity opportunities, aligning employee interests with the company's long-term success.
How to Stand Out
- Ensure your resume highlights specific experience with AI infrastructure, team leadership, and technical expertise.
- Prepare examples of how you've led cross-functional teams and driven technical decisions in previous roles.
- Develop a portfolio that showcases your ability to measure AI quality, detect regressions, and improve performance.
- Emphasize your understanding of the latest advancements in AI and how you've applied them to solve real-world problems.
- Be prepared to discuss your approach to balancing short-term product needs with long-term platform investments.
- Highlight any experience with statistical experimentation, A/B model testing, or model benchmarking.
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