Staff Ai Engineer

Summary

Join Lattice's AI Engineering team and lead the charge in shaping Lattice's artificial intelligence strategy. You will design and build end-to-end AI/ML solutions, develop and optimize LLM-based applications, and drive architectural decisions. This role requires collaboration with various teams, mentoring junior engineers, and leading technical evaluations of AI/ML vendors. You will need extensive experience in AI/ML, strong programming skills in Python, and expertise in MLOps and AWS. The estimated annual salary is $187,500 - $234,500, and the position includes stock options and a comprehensive benefits package.

Requirements

• Have 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
• Have deep expertise in AI/ML concepts, including LLMs, model fine-tuning, and traditional ML techniques (supervises / unsupervised systems or neural networks)
• Have experience with advanced LLM techniques: Retrieval-Augmented Generation (RAG), RLHF , or LoRA
• Have strong programming skills in Python, with hands-on experience in frameworks like PyTorch, TensorFlow, Hugging Face Transformers, or LangChain
• Have expertise in MLOps: deployment (Docker, Kubernetes, Terraform and/or CDK), model monitoring (MLflow, DataDog, etc), and CI/CD workflows
• Be proficient in the AWS ecosystem (Lambdas, SQS, SNS, etc) and data engineering tools for large-scale datasets
• Have excellent problem-solving, system design, and technology decision-making skills
• Have strong communication and collaboration skills to lead projects and mentor junior team members, and to also collaborate with product and executives

Responsibilities

• Lead and shape Lattice's artificial intelligence strategy
• Build software to help the humans powering organizations thrive, with a particular focus on large language models (LLMs) and emerging machine learning technologies
• 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

Preferred Qualifications

• Have experience with agentic AI or building multi-agent systems
• Have experience with cloud-based ML services (e.g., AWS SageMaker, Google Cloud AI, Azure Machine Learning)
• Have experience with TypeScript / Javascript as it is our current programming language (Our current stack includes NodeJS, GraphQL, and PostgreSQL. We rely on AWS to host our infrastructure)
• Have professional experience in at least two cloud platforms (AWS, GCP, Azure)
• Have knowledge of optimization and scaling tools like Ray, Spark, or distributed training systems
• Have familiarity with hybrid solutions combining traditional ML and LLMs
• Have a 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
• Incentive stock options