Software Engineer, Frontend (Agentic AI)

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Full Time Remote friendly

Software Engineer, Frontend (Agentic AI)

Sift

• Remote

Match score —

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Role snapshot

Compensation $160,000 - $200,000

Location Remote Work from anywhere

Technologies

• AWS
• Azure
• GCP
• Kubernetes
• Docker
• Terraform
• GitHub Actions

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Job Description About Sift

Sift is the data infrastructure platform for hardware engineering teams. We turn high-frequency telemetry into engineering insights for mission-critical machines: rockets, satellites, autonomous vehicles, energy systems, and defense platforms. Founded by former SpaceX engineers, we are building the review and analysis layer for the AI era of physical systems.

About The Role Hardware programs generate far more telemetry than any team can review by hand. Sift Agents is our answer: AI agents that work alongside hardware engineers, investigating anomalies, reviewing test and flight data, and answering in minutes questions that used to take a day of scripting.

This role comes with real product ownership and autonomy. You will talk directly to customers to understand how they review their machines, decide what to build, and own it from first MVP through every iteration after it ships. The surface area is wide: one day you might be polishing the micro-interactions that make the chat experience feel great, the next you might be building a bespoke caching layer for the chat messages off the main JS thread. We’re heavy users of frontier agentic products ourselves and have strong opinions about what makes them great. Sift Agents is where we put those opinions to work.

This is a product engineering role, not a research role. Most of the work is the hard part of making agents feel dependable in the browser: streaming interactions, long-running tasks, rendering agent output over large real-time datasets, and showing engineers exactly what an agent did and why.

In This Role, You’ll

• Talk directly to customers and partner with product to turn real review workflows into agent capabilities: generating dashboards, writing analysis scripts, and surfacing insights buried in their telemetry
• Build the frontend surfaces where Sift Agents live, and make them feel great
• Design the interaction patterns of agentic UX: streaming responses, long-running tasks, interruptions, and showing an agent’s work so engineers can trust it
• Render an agent’s findings alongside the telemetry that backs them, and keep it fast even when the data is large
• Push the browser to its limits when the data demands it: Web Workers, OPFS-backed caching, and stepping outside React when the framework becomes the bottleneck
• Contribute to the component library to keep agentic UI patterns consistent across the product
• Collaborate with backend and full stack engineers on the API design that powers agent sessions

The Skillset You’ll Bring

• 3+ years of professional software engineering experience
• Get excited about owning a product area: talking to customers, deciding what to build, and shipping it
• Have built complex, high-performance web applications with technologies like React, NextJS, TypeScript, or similar
• Have an eye for detail: you notice the micro-interactions, latency, drops in FPS, and polish that separate good interfaces from exceptional ones
• Are curious about new AI products: you try new agents, models, and features as they ship, and have opinions about what makes them good

If this role excites you, apply even if you don’t check every box.

Bonus Points

• Shipped products to users at scale: large data volumes, significant active user counts, or deep technical complexity
• Shipped LLM-powered features
• Built chat or agentic interfaces: streaming responses, tool-call rendering, long-running tasks
• A strong understanding of web performance optimization and browser rendering
• Worked with modern CSS (Tailwind) and component libraries (Radix UI) to build design systems
• Used technical visualization tools (WebGL, D3.js, Apache ECharts), WebAssembly, and time-series data
• Built tools for technical users (dashboards, data-editing environments)
• A personal ecosystem of AI dev tooling: custom agents, skills, scripts, or workflows built to ship faster
• A background in scientific computing or …