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Staff AI Engineer

This is Engineering at Lattice

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.

What You Will Do

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.

  • You will design and build end-to-end architectures for AI/ML solutions, including data pipelines, model development, and production deployment.
  • You will develop, fine-tune, and optimize LLM-based solutions for Lattice’s talent platform and product suite.
  • You will drive architectural decisions, balancing trade-offs between scalability, latency, accuracy, and cost.
  • You will implement AIOps practices, including CI/CD pipelines, feature flagging, model monitoring, and performance optimization.
  • You will 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.
  • You will 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.
  • You'll 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.

What You Will Bring to the Table

  • You 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.
  • You have deep expertise in LLM concepts including prompt engineering, AI feature evaluation metrics, model fine-tuning, knowledge of vector DBs, etc. 
  • You have experience with advanced LLM techniques, at a minimum with Retrieval-Augmented Generation (RAG), and understanding or exposure to RLHF, or LoRA.
  • You have experience or knowledge of ML traditional techniques (supervised / unsupervised systems or neural networks) and be able to pin point when a solution requires an LLM solution or an ML solution
  • You have strong programming skills in Python, with hands-on experience in frameworks like PyTorch, TensorFlow, Hugging Face Transformers, or LangChain.
  • You have expertise in MLOps: deployment (Docker, Kubernetes, Terraform and/or CDK), model monitoring (MLflow, DataDog, etc), and CI/CD workflows.
  • You are proficient in the AWS ecosystem (Lambdas, SQS, SNS, etc) and data engineering tools for large-scale datasets.
  • You have excellent problem-solving, system design, and technology decision-making skills.
  • You have strong communication and collaboration skills to lead projects and mentor junior team members, and to also collaborate with product and executives.

Nice to Have

  • 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 (Our current stack includes NodeJS, GraphQL, and PostgreSQL. We rely on AWS to host our infrastructure)
  • 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

 

The estimated annual cash salary for this role is $187,500 - $234,500. This position is also eligible for incentive stock options, subject to the terms of Lattice’s applicable plans.

Benefits: The Company offers the following benefits for this position, subject to applicable eligibility requirements: 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; and Invest in Your People Fund

*Note on Pay Transparency:

Lattice provides an estimate of the compensation for roles that may be hired as required by state regulations. Compensation may vary based on (a) location, as Lattice factors in specific location when benchmarking compensation for most roles; (b) individual candidate skills and qualifications; and (c) individual candidate experience.

Additionally, Lattice leverages current market data to determine compensation, so posted compensation figures are subject to change as new market data becomes available. The salary, other compensation, and benefits information is accurate as of the date of this posting. Lattice reserves the right to modify this information at any time, subject to applicable law.

About Lattice

Lattice is on a mission to build cultures where employees and their companies thrive. In an age where employees have more choices than ever before, businesses that put employees first are winning 🏅– and Lattice is building the tools to empower those people-centric companies.

Lattice is a people success platform that offers performance reviews, employee engagement surveys, real-time feedback, weekly check-ins, goal setting, and career planning in a way that allows companies to focus on employee development, growth, and engagement – yielding stronger employee retention, performance, and impact to the bottom line 📈. Since launching in 2016, we have grown to over 5,000+ customers globally, including brands like Loom, Robinhood, and Gusto. 


Lattice is committed to equal treatment and opportunity in all aspects of recruitment, selection, and employment without regard to gender, race, religion, national origin, ethnicity, disability, gender identity/expression, sexual orientation, veteran or military status, or any other category protected under the law. Lattice is an equal opportunity employer; committed to a community of inclusion, and an environment free from discrimination, harassment, and retaliation.

By clicking the "Submit Application" button below, you consent to Lattice processing your personal information for the purpose of assessing your candidacy for this position in accordance with Lattice's Job Applicant Privacy Policy.

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Average salary estimate

$211000 / YEARLY (est.)
min
max
$187500K
$234500K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Staff AI Engineer, Lattice

If you're a Staff AI Engineer looking for an exciting opportunity to make a significant impact, look no further than Lattice! As a remote employee in the US, you’ll join a dynamic Engineering team dedicated to crafting cutting-edge products that enhance the employee experience in organizations. Here at Lattice, we prioritize maintainable, robust, and efficient code while fostering a collaborative environment that bridges product managers, designers, and engineers. In this role, you'll lead the charge in shaping our AI strategy, focusing on large language models (LLMs) and innovative machine learning technologies. You’ll design comprehensive AI/ML solutions, create efficient data pipelines, and ensure that production deployments are smooth and effective. Your expertise in LLMs and advanced techniques will help optimize solutions for our talent platform. Moreover, you’ll play a vital role in steering our engineering practices, implementing AIOps, and guiding your peers through mentorship. If you're someone who thrives on collaboration and values technical excellence, then Lattice is the place for you. Join us in our mission to empower employee success and drive impactful decision-making through AI!

Frequently Asked Questions (FAQs) for Staff AI Engineer Role at Lattice
What responsibilities does a Staff AI Engineer at Lattice have?

As a Staff AI Engineer at Lattice, you'll be responsible for leading the development of AI-driven features, designing end-to-end architectures for AI/ML solutions, and optimizing large language models for our talent platform. Your role will also involve driving architectural decisions, collaborating cross-functionally, and mentoring junior engineers.

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What qualifications are needed for the Staff AI Engineer position at Lattice?

To qualify for the Staff AI Engineer role at Lattice, you should have over 8 years of experience in software engineering, with at least 4 years focused on building AI/ML solutions. Expertise in LLMs, strong Python programming skills, and familiarity with MLOps practices are essential. Experience with advanced techniques and working in cloud ecosystems, especially AWS, is highly valued.

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What does Lattice offer to Staff AI Engineers in terms of salary and benefits?

Lattice offers a competitive salary for the Staff AI Engineer role, estimated between $187,500 to $234,500 annually. Additional benefits include medical, dental, and vision insurance, paid parental leave, a 401(k) retirement plan, wellness apps, learning and development budgets, and more, creating a comprehensive work-life balance.

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How does Lattice's culture support Staff AI Engineers?

At Lattice, the culture is built around collaboration, innovation, and continuous improvement, allowing Staff AI Engineers to thrive. The environment encourages feedback, mentorship, and intersectional teamwork, fostering personal growth and professional development while supporting the overall mission of empowering organizations.

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What tools and technologies should a Staff AI Engineer at Lattice be familiar with?

A Staff AI Engineer at Lattice should be well-versed in Python, and frameworks like PyTorch and TensorFlow. Additionally, expertise in MLOps tools, Docker, Kubernetes, and familiarity with AWS services, as well as programming in TypeScript or JavaScript, can greatly enhance the ability to contribute successfully to the team.

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Common Interview Questions for Staff AI Engineer
Can you describe your experience with large language models?

In your response, focus on your hands-on projects involving LLMs, discussing specific models you’ve worked with, how you implemented prompt engineering, and any success you had in optimizing model performance.

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How do you approach designing an end-to-end AI/ML architecture?

Detail your process, which may include requirements gathering, designing data pipelines, model selection, deployment strategies, and plans for monitoring and optimizing the performance of the model post-deployment.

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What is your experience with AIOps practices?

Share specific examples of AIOps practices you've implemented, such as CI/CD workflows, model performance monitoring, and how you’ve optimized deployments to improve operational efficiency.

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How do you decide between using an LLM solution and traditional ML techniques?

Discuss your approach to evaluating business requirements, dataset characteristics, and the specific outcomes desired to guide your decision-making process between LLM and traditional ML solutions.

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What programming languages and tools are you proficient in?

Highlight your experience with Python, any frameworks you’re comfortable with like PyTorch and TensorFlow, and demonstrate familiarity with MLOps tools and cloud platforms, particularly within the AWS ecosystem.

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Can you explain the fine-tuning process for AI/ML models?

Explain your methodology for fine-tuning models, including factors such as training data selection, adjusting hyperparameters, and performance evaluation metrics you typically use to measure success.

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How do you handle trade-offs between scalability and accuracy in your projects?

Illustrate your understanding of the balance needed between scalability and accuracy, providing examples of how you’ve approached these challenges in past projects, including any specific methodologies you've employed.

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Why is collaboration important in AI/ML projects?

Respond by emphasizing the complexities of AI/ML projects that require cross-disciplinary collaboration, and share experiences or specific examples where collaboration led to improved results or innovations.

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What strategies do you use for effective mentoring in AI engineering?

Discuss your personal mentoring philosophy and share strategies you find effective, such as setting clear goals, providing constructive feedback, and encouraging problem-solving through guided discussions.

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How do you stay updated with the latest advancements in AI technology?

Mention resources you rely on for staying current, such as following industry leaders, participating in online communities, attending conferences, or contributing to research papers, underlining your commitment to continuous learning.

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Our mission is to make work meaningful. We believe that good performance management is critical for companies and employees to be successful. Unfortunately, the process is often painful, but we don’t think it has to be that way. By streamlining t...

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DATE POSTED
April 12, 2025

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