Engineering Manager, Lattice

• 8+ years of professional experience in software engineering, with at least 3 years in managing engineering teams
• Proven ability to inspire, mentor, and develop high-performing teams
• Track record of aligning technical work with organizational goals and driving impactful outcomes
• Exceptional verbal and written communication skills, with an adjustable style to executives, engineers and non technical staff
• Ability to navigate complex discussions and build consensus across departments
• Hands-on experience designing and deploying scalable AI/ML solutions, particularly LLMs, in production environments
• Proficiency in Python, AI/ML frameworks such as TensorFlow, Transformers, LangChain, etc), and LLM techniques such as prompt engineering, RAG, Fine tuning, etc
• Strong knowledge of cloud platforms, preferably AWS, infrastructure tools like Docker and Kubernetes
• Strong knowledge of AIOps tools such as Docker, Kubernetes, Terraform/CDK, MLflow, and DataDog for deployment, monitoring, and CI/CD workflows

Desirable

• As a Manager, you will lead a team of engineers dedicated to building impactful AI solutions. Your role will combine technical expertise, architectural leadership, and people management to shape our AI initiatives and drive organizational success for the Lattice people platform
• Translate company strategy into actionable team goals and objectives, aligning technical initiatives with organizational priorities
• Manage, coach and inspire a team of 5-10 engineers, fostering a culture of collaboration, innovation, learning and growth
• Mentor and coach engineers, promoting technical growth and aligning their development with team & company objectives
• Drive business and architecture decisions by keeping up with emerging trends in generative AI, reinforcement learning, or multi-agent systems
• Lead the design and development of AI solutions, with a strong focus on large language models (LLMs) and machine learning
• Provide hands-on technical guidance to the team, including model development, integration, and optimization
• Drive end-to-end delivery of AI/ML projects, with architecture decisions that ensure cost-efficiency, scalability, reliability, security and business impact
• Bring a relentless passion for continuous improvement for both engineering craft and processes
• Build an inclusive and psychologically safe team environment, fostering diverse perspectives and innovation