Applied AI Engineer

Laurel

Applied AI Engineer to enhance AI features for Laurel's AI Time platform. Collaborating with cross-functional teams on product development and user engagement.

Posted 7/20/2026full-timeRemote • California, New York • 🇺🇸 United StatesSeniorLead💰 $254,000 - $328,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in LLM Application Engineering, Evaluation, and Retrieval & Embeddings, with a strong focus on delivering high-quality AI features. Proven ability to engage with cross-functional teams and customers to define success metrics and drive product improvements.

Highest-signal resume keywords

LLM Application EngineeringEvaluation MetricsRetrieval & EmbeddingsPython ProgrammingAI Coding Tools

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

LLM Application EngineeringEvaluation MetricsRetrieval & EmbeddingsPython ProgrammingTypeScript ProgrammingNode.jsMongoDBMessage QueuesContext AssemblyPrompt Optimization

Soft Skills

Analytical SkillsProblem-Solving SkillsCommunication SkillsCollaboration SkillsCustomer Mindset

Tools & Technologies

Claude CodeCursorCopilotAgentic Coding

Industry Keywords

AI FeaturesMachine LearningSemantic RetrievalGolden DatasetsNorth-Star Metrics

Tech Stack

Tools & technologies

AssemblyJavaScriptMongoDBNode.jsPythonTypeScript

About the role

Key responsibilities & impact

Own AI features end-to-end, from problem statement to GA
Move features through our rollout tiers (prototype → design partner → beta → GA), earning each promotion with an eval baseline and a capacity plan
Build and defend evals: golden datasets, a north-star metric per feature, and online monitoring — so we can *see and prove* how a feature behaves, not guess
Lead the "meaning" layer of our semantic stack: retrieval semantics, embedding quality (proven first on initiative-candidate retrieval), and the label flywheel that feeds prompt optimization and golden sets. You co-design our vector and knowledge-graph stores with the AI Platform team — you're their most demanding customer
Push output quality with the levers that matter: context assembly, prompt optimization, and per-customer/per-firm generation
Work closely with cross-functional teams — product managers, designers, and other engineers — to gather requirements, define measures of success, and deliver high-quality solutions
We want you not just to build but to *engage* with our product and our users. Your input and opinion will be highly valuable, and it is expected that you have many thoughts on how things should be done and why

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
7+ years of professional software engineering experience, including a track record of shipping ML/LLM-powered features to production and owning their quality
You **think in problems, not solutions** — you can take a half-formed prototype and find the real customer problem behind it
Have *deep knowledge and understanding*, as well as *strongly-held opinions* about some of the below areas (or similar). We want to hear your thoughts on best practices, patterns, failure modes, and how you *consistently* ship AI features of the *highest* quality. What would you teach our other engineers? What has bitten you in the past?
**LLM application engineering:** prompting, structured outputs, retrieval/context assembly (RAG), agentic workflows
**Evaluation:** golden datasets, offline harnesses and online monitoring, north-star metrics — measuring quality rather than eyeballing it
**Retrieval & embeddings:** vector search, semantic retrieval quality, and the data/label flywheel that improves it
**Languages & stack:** strong in Python and/or TypeScript; comfortable across a modern backend (Node.js / NestJS, MongoDB, message queues) — nice to have given our stack
You use **AI coding tools** fluently in your daily work (Claude Code, Cursor, Copilot, agentic coding) and have a point of view on where they accelerate real engineering and where they don't
Strong analytical and problem-solving skills, with the ability to think critically and creatively. Ability to work in a fast-paced, dynamic environment and manage multiple priorities
Excellent communication and collaboration skills, with the ability to work effectively in a team-oriented environment
A customer mindset with proven ability to engage with customers and understand their needs.

Benefits

Comp & perks

Great employee benefits, including equity and 401K
Bi-annual, in-person company off-sites, in unique locations, to grow and share time with the team
An opportunity to perform at your best while growing, making a meaningful impact on the company's trajectory, and embodying our core values: understanding your "why," dancing in the rain, being your whole self, and sanctifying time