AI Developer, Awesome Motive

• You're a builder at heart. You don't just use AI tools - you understand how they work under the hood, and you think about how to make them useful for real people, not just technically impressive
• You're a self-starter who can take a loosely defined problem, figure out the right approach, and ship a working solution without needing to be told what to do next
• You think about the user and the decision first, not the pipeline and the model. When you see data, your first instinct is to ask what question it answers for the person who needs it
• You're comfortable owning the full stack of an AI project - from data exploration and model selection to building the API, deploying the service, and making sure it actually works in production
• You're an excellent communicator, fluent in both verbal and written English. You can explain complex technical decisions to non-technical stakeholders without dumbing it down
• You have the curiosity and desire to learn and grow your skills. The AI landscape moves fast and you keep up because you genuinely enjoy it, not because someone tells you to
• You take pride in the quality and craftsmanship of your work - clean code, proper error handling, thoughtful architecture, not just something that works on the happy path
• You're a team player who is comfortable working alongside other developers and doesn't take critical feedback personally
• You're excited about building internal tools and data systems that may not have a flashy frontend but have massive impact on how an organization operates
• 3+ years of professional experience building AI/ML systems in production environments (not just POCs or hackathon projects)
• Strong proficiency in Python, including production-grade practices - proper packaging, testing, type hints, async where appropriate
• Hands-on experience with LLM frameworks and tools: LangChain, LlamaIndex, or similar. You should be able to build a RAG pipeline from scratch
• Experience with vector databases (Pinecone, ChromaDB, FAISS, Qdrant, or similar) and embedding models
• Solid understanding of ML fundamentals - not just API calls, but how models work, when to fine-tune vs prompt engineer, how to evaluate properly
• Experience building and deploying APIs (FastAPI, Flask, or similar) that serve ML models in production
• Familiarity with cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
• Experience with data processing at scale - SQL, pandas, Spark, or similar
• Competent with version control through Git and GitHub. Clean commit history, proper branching, code review through PRs
• The ability to iterate and ship ideas quickly without sacrificing code quality
• Exceptional troubleshooting skills - when something breaks in production at scale, you can diagnose it
• Ability to keep complex systems simple. Simplicity is a core value
• Previous remote work experience. You know how to manage your time, communicate proactively, and stay productive without supervision
• Personal computer with reliable internet access
• Availability to participate in audio/video meetings and be available on Slack between the hours of 9 AM - 1 PM EST daily

Desirable

• As an AI-First Developer on the R&D team, you will build AI-powered internal tools and data-driven systems that help teams across the organization make better decisions
• You will work with behavioral and operational data from over 30 million websites that use our products - WPForms, MonsterInsights, OptinMonster, Easy Digital Downloads, and more - and turn that data into analytics platforms, reporting automation, workflow intelligence, and AI-powered features that real teams use every day
• This is not a WordPress development role
• WordPress familiarity is a bonus for product context, but the core of this role is AI/ML engineering on top of an extraordinary data asset
• You will sit between a Full Stack AI Developer and an AI ML Engineer - strong enough on the ML and data side to work intelligently with large-scale operational data, and product-minded enough to build tools that teams actually adopt
• Building AI-powered internal tools and data-driven systems used across the organization - analytics platforms, reporting automation, workflow intelligence
• Developing AI/ML-driven platforms that process and analyze large-scale operational data from 30M+ sites across our product suite
• Designing and deploying RAG systems, LLM-powered features, and agentic workflows that generate actionable insights for internal teams
• Building data pipelines that ingest, transform, and serve behavioral and operational data at scale
• Prototyping and shipping AI solutions that streamline internal processes, reduce manual effort, and improve decision-making
• Evaluating and selecting the right models, frameworks, and infrastructure for each use case - balancing performance, cost, and latency
• Writing clean, well-tested, production-grade Python code with proper error handling, logging, and observability
• Collaborating with product teams and stakeholders to understand what they need, then building tools they actually use
• Keeping up with the rapidly evolving AI landscape and bringing new ideas, tools, and approaches to the team
• Communicating with the team and supporting your peers using chat, audio, and video

• If all of this sounds interesting, then please submit your application!
• Please clearly include the following in your cover letter:
• A brief walkthrough of your AI/ML journey - where you started, what you've built, and what kind of work excites you most
• The most impactful AI system you've built in production. What did it do, who used it, and what made it hard?
• If you had access to behavioral data from 30 million websites - form submissions, conversion flows, email engagement, plugin usage - what is the first thing you would build and why?
• Profile links with code samples (GitHub, GitLab, personal repos, published packages, etc)
• Links to any published research, technical blog posts, or open-source contributions
• Other profile links if available (your website, Twitter/X, LinkedIn, etc)
• Tell us a bit about yourself and why you should be considered. Details about your experience, qualifications, personality, etc are very helpful
• Also note, don't forget to proofread before submitting. Check spelling, capitalization, etc. This is your chance to make your application stand out :)