The Role
Lead the intelligence layer for a real-time voice AI agent: design and optimize model orchestration, prompt engineering and evals, build agentic workflow orchestration, ensure LLM reliability and regression testing, and select/optimize speech and LLM models balancing quality, latency, and cost.
Summary Generated by Built In
About Luminade
We're building the conversational voice layer for how people work. People have found dictation useful for input and text-to-speech useful for output. We're going further: a single conversation you never have to step out of, where you get responses back and actually get things done.
We started with email, the place where most work actually lives. Now we're expanding to calendar, documents, and more, so our AI has complete context on what matters in a person's day. The goal is simple: let people work without being hostage to a screen.
We're building first for people with vision impairment, ADHD, and dyslexia, communities where this kind of interface isn't a nice-to-have. But this is not a niche product. The same way curb cuts were designed for wheelchair users and ended up benefiting everyone, we're using accessibility as the design constraint that forces us to build something genuinely better. The endgame is hundreds of millions of sighted users who want to stay productive during their commute, away from a screen, or simply in flow.
The TeamOur CEO, Sriram, is an engineer and entrepreneur (1 exit) who started this company because of his own experience with vision loss. He knows this problem from the inside. Our CTO, Mikhail, is a former Google engineer and four-time world champion in competitive skydiving. He brings the same precision and intensity to systems architecture that he brings to everything else.
We're backed by South Park Commons, have raised $2M, and work in-person in San Francisco.
What You'll OwnThe quality of our AI agent IS the product. You'll own the intelligence layer — this isn't a research role. This is the person who makes the agent reliable, fast, and smart enough that users trust it with their actual work.
The voice agent pipeline. Designing and optimizing the full model orchestration chain for real-time, low-latency conversational interactions. You'll decide which models to use, how to stitch them together, and how to make the whole thing feel instant.
Prompt engineering and evals. Crafting, testing, and iterating on prompts across the product. Building eval frameworks that catch regressions before users do.
Agentic workflow orchestration. Building the multi-step reasoning and action-taking capabilities that let users manage email, calendar, and documents through natural conversation. Context management, memory, and knowing when the agent should act versus ask.
LLM reliability and regression testing. LLMs are nondeterministic. You'll build the systems that ensure consistent, high-quality responses across thousands of user interactions.
Model selection and optimization. Evaluating and integrating the right LLMs, speech-to-text, text-to-speech, or speech-to-speech models. Making hard tradeoffs between quality, latency, and cost at every layer of the stack.
What We're Looking ForYou've worked deeply with AI/ML in production and felt the pain of making these systems reliable at scale. You've shipped LLM-powered applications where model output goes directly to humans, not dashboards. Ideally you've built real-time or voice AI systems — but more than any specific experience, you take initiative, you ship, and you think about the person on the other side of every interaction.
CompensationThe base pay range for this role is $150,000 – $250,000 per year.
Skills Required
- Deep production experience with AI/ML and shipping LLM-powered applications
- Experience designing and optimizing model orchestration chains for real-time, low-latency conversational interactions
- Experience with prompt engineering and building eval frameworks to catch regressions
- Experience building agentic workflow orchestration, context management, and memory systems
- Experience ensuring LLM reliability and automated regression testing across user interactions
- Experience evaluating and integrating LLMs and speech models (speech-to-text, text-to-speech, speech-to-speech)
- Ability to take initiative, ship product, and focus on user experience
- Prior experience with real-time or voice AI systems
- Willingness to work in-person in San Francisco
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The Company
What We Do
Luminade is building a voice-first AI assistant designed to help users manage digital work—such as email, calendar, and documents—without needing to rely on a screen. The company focuses on accessibility, aiming to support individuals with vision impairment, ADHD, and dyslexia, while also providing a productivity tool for all users to stay efficient while away from their screens or in flow.
