Principal Applied AI Engineer

About Us

Venice is the world’s leading consumer AI company built on principles of privacy, free speech, and user sovereignty.

We’re building the Port City of AI, in which millions of individuals and AI agents gather, interact, and access sophisticated AI resources on a private and permissive foundation.

Joining Venice means joining a team of unorthodox builders who believe in moving quickly, delivering a beautiful mass-market consumer product that doesn’t spy on people or censor their ideas and questions., If you’re energized by big ideas, entrepreneurial spirit, individual empowerment, and the opportunity to help shape a fast-growing company in the world’s hottest industry from the ground up, please reach out..

Why We’re Hiring

Venice is growing fast. Revenue is accelerating, our team is expanding, and the demands on every department, from engineering to marketing to operations to finance, are scaling with us.

We believe the next leap in our company’s efficiency won’t come from hiring our way out of every bottleneck. It will come from giving every team the tools to build and deploy AI agents that multiply what they can accomplish.

We’re hiring a Principal Applied AI Engineer to build the internal agent platform that makes this possible across the entire company. This is not a role scoped to engineering tooling alone. The departments that need the most help right now, marketing, support, communications, operations, and finance, are outside of engineering. You’ll build the platform they use to help themselves.

This is a solo individual contributor role to start, reporting directly to Jesse Proudman, Co-Founder. As the company grows and the platform matures, this role has a clear path to building and leading a team.

You’ll be the person who decides how Venice builds its internal agent platform: whether that means wiring up commercial solutions (as long as they run on Venice’s inference), building orchestration frameworks from the ground up, or some combination. The space is novel. There may not be commercial solutions yet. That’s fine. You’ll help us figure it out.

What You’ll Do

Build the internal agent platform. Design and ship the foundational infrastructure that teams across the company use to create, deploy, and manage their own AI agents. This includes agent templates, shared tool libraries, retrieval systems, orchestration patterns, eval pipelines, and the abstractions that let non-engineers assemble useful agents without writing code. The goal: departments growing their output via agents they built on your platform, not solely via headcount.

Decide the build-vs-orchestrate strategy. Evaluate commercial agent platforms, frameworks, and tools. Where existing solutions work and can run on Venice’s inference, use them. Where they don’t exist or don’t meet our needs, build from the ground up. You own this decision space.

Dogfood Venice’s own platform. The internal agent platform you build should run on Venice’s inference API and models. We are our own first customer. This isn’t a branding exercise; it’s a product development advantage. The agents your colleagues deploy internally will surface edge cases, performance needs, and feature gaps that make Venice’s platform better for external developers too.

Solve the data privacy problem. This is our biggest constraint. Venice’s brand is built on privacy and user sovereignty. Our internal agents must operate without leaking company data to third-party model providers. You’ll architect the platform so that agents run on our own inference, data stays within our infrastructure, and access controls prevent cross-department data leakage. This is not an afterthought; it is a core design requirement from day one.

Make it usable by non-engineers. The platform’s success depends on adoption. Marketing managers, support leads, and finance analysts should be able to use your platform to build agents that solve their own problems. That means clean abstractions, sensible defaults, good documentation, and a UX layer that hides complexity without removing power. You’re building a product, and your internal colleagues are your users.

Partner with every team to understand their needs. Work directly with marketing to understand their content and research workflows. Work with support to understand triage and response patterns. Work with operations on workflow automation. Work with finance on data extraction and reporting. You’ll need to understand each team’s pain points well enough to design platform capabilities that let them build agents that actually help.

Evaluate, iterate, and prove ROI. Measure the impact of the platform across the company. Close the loop between production traces, evaluations, and platform design. Optimize for quality, latency, and cost. Show the company, in concrete terms, how agents built on your platform are multiplying human output.

Evangelize and educate. Help non-engineering teams understand what’s possible with the platform. Run workshops, write internal docs, and build proof-of-concept demonstrations that make the abstract concrete. The adoption challenge is as important as the technical one.

Who You Are

You’re a senior software engineer first. You have deep experience building production systems. Venice’s stack is Rust, TypeScript, Go, and Python, in that order of preference. You should be fluent in at least two of these and comfortable picking up the rest. You understand distributed systems, API design, data pipelines, and how to operate things reliably at scale. AI is a tool you wield, not a research project you observe.

You’ve built using LLMs and agents in production. You have hands-on experience with LLM APIs, agent orchestration, tool calling, retrieval-augmented generation, prompt design, and evaluation frameworks. You’ve taken agent systems from prototype to production and dealt with the messy realities: hallucinations, latency, cost, context limits, and edge cases.

You think like a platform engineer, not a consultant. You build infrastructure that other people use to solve their own problems. You care about abstractions, developer experience, and making complex things simple. You measure success by how many people build on your platform without needing to ask you for help.

You’re comfortable with ambiguity and novelty. This space doesn’t have established best practices yet. You won’t find a playbook for “internal agent platform for a consumer AI company.” You’re comfortable making architecture decisions without a clear precedent and adjusting course when you learn more.

You think about data privacy as a system design problem. You understand the technical and architectural implications of keeping data within a controlled boundary. You’ve worked with access controls, data classification, and the tradeoffs between utility and confidentiality.

You build products for non-technical users. You can sit down with a marketing manager, understand their workflow, and build platform capabilities that let them create an agent that makes them 3x more productive. You communicate clearly without jargon. You enjoy teaching and evangelizing. You measure your success by their adoption.

You’re excited about dogfooding. You want to use Venice’s own models and inference API as the foundation for the platform you build. You see internal tooling as a way to stress-test and improve the platform, not just as a cost center.

You have opinions about build vs. buy, but you’re not dogmatic. You’ve worked with agent orchestration frameworks and custom-built tooling. You’ve seen where off-the-shelf solutions accelerate you and where they become a constraint. You can articulate when to build custom and when to orchestrate, and you don’t fall in love with either approach ideologically.

You move fast. You prefer a working prototype this week over a perfect architecture document next month. You iterate in production. You ship, measure, and adjust.