Staff AI Engineer

About the position

Lattice's Engineering team is continuously working to better both our product and our craft. We use a modern, cutting-edge tech stack aimed at developer productivity and delight. We strive for maintainable, robust, and performant code. We're highly collaborative and continuously iterative and work closely with designers and product managers. We prioritize not only great technical architecture but also an amazing product experience. You will join Lattice's AI Engineering team, where you will lead and shape Lattice's artificial intelligence strategy while building software to help the humans powering organizations thrive, with a particular focus on large language models (LLMs) and emerging machine learning technologies.

Responsibilities

• Design and build end-to-end architectures for AI/ML solutions, including data pipelines, model development, and production deployment.
• Develop, fine-tune, and optimize LLM-based solutions for Lattice's talent platform and product suite.
• Drive architectural decisions, balancing trade-offs between scalability, latency, accuracy, and cost.
• Implement AIOps practices, including CI/CD pipelines, feature flagging, model monitoring, and performance optimization.
• Work at a strategic level to influence technical decisions by collaborating cross-functionally with product managers, data scientists, and engineers to deliver AI-driven features aligned with business goals.
• Mentor and guide engineers of various experiences in AI engineering, establishing best practices for software and AI development, standardizing and evangelizing AI engineering in our team.
• Lead technical evaluation of AI/ML vendors and platforms, making strategic recommendations on build vs. buy decisions for our AI infrastructure, from LLM providers to security and monitoring solutions.

Requirements

• 8+ years of professional experience writing and maintaining production-level applications, with at least 4 years in designing and implementing scalable AI/ML systems in production.
• Deep expertise in LLM concepts including prompt engineering, AI feature evaluation metrics, model fine-tuning, knowledge of vector DBs, etc.
• Experience with advanced LLM techniques, at a minimum with Retrieval-Augmented Generation (RAG), and understanding or exposure to RLHF, or LoRA.
• Experience or knowledge of ML traditional techniques (supervised / unsupervised systems or neural networks) and be able to pinpoint when a solution requires an LLM solution or an ML solution.
• Strong programming skills in Python, with hands-on experience in frameworks like PyTorch, TensorFlow, Hugging Face Transformers, or LangChain.
• Expertise in MLOps: deployment (Docker, Kubernetes, Terraform and/or CDK), model monitoring (MLflow, DataDog, etc), and CI/CD workflows.
• Proficient in the AWS ecosystem (Lambdas, SQS, SNS, etc) and data engineering tools for large-scale datasets.
• Excellent problem-solving, system design, and technology decision-making skills.
• Strong communication and collaboration skills to lead projects and mentor junior team members, and to also collaborate with product and executives.

Nice-to-haves

• Familiarity with hybrid solutions combining traditional ML and LLMs.
• Experience with agentic AI or building multi-agent systems.
• Experience with cloud-based ML services (e.g., AWS SageMaker, Google Cloud AI, Azure Machine Learning).
• Experience with TypeScript / Javascript as it is our current programming language.
• Professional experience with multiple cloud platforms (AWS + others such as Azure or GCP).
• Track record of publishing or presenting on artificial intelligence and machine learning topics in professional forums.

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• Life, AD&D, and Disability Insurance
• Emergency Weather Support
• Wellness Apps
• Paid Parental Leave
• Paid Time off inclusive of holidays and sick time
• Commuter & Parking Accounts
• Lunches in the Office
• Workplace Amenities Stipend
• Internet and Phone Stipend
• One time WFH Office Set-Up Stipend
• 401(k) retirement plan
• Financial Planning
• Learning & Development Budget
• Sabbatical Program
• Invest in Your People Fund