Full-Time
Senior Software Engineer
Frontend, Agentic AI
SIFT
51-200 employees
Automated certification and compliance platform
Compensation Overview
$180k - $230k/yr
No H1B Sponsorship
San Francisco, CA, USA + 1 more
More locations: Marina Del Rey, CA, USA
Hybrid
Two in-office days per week, Mondays and Thursdays, plus one full in-person week every two months. Relocation to Los Angeles is supported, or candidates may work from the San Francisco office.
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- At least 8 years of professional software engineering experience.
- Experience owning a product area, including talking to customers, deciding what to build, and shipping it.
- Experience building complex, high-performance web applications with technologies such as React, NextJS, TypeScript, or similar.
- An eye for detail regarding micro-interactions, latency, frame-rate drops, and interface polish.
- Curiosity about new artificial intelligence products, including trying new agents, models, and features as they ship, and forming opinions about their quality.
- Talk directly to customers and partner with product to turn real review workflows into agent capabilities, including generating dashboards, writing analysis scripts, and surfacing insights buried in telemetry.
- Build the frontend surfaces where Sift Agents operate and improve their usability and quality.
- Design interaction patterns for agentic user experiences, including streaming responses, long-running tasks, interruptions, and showing an agent’s work so engineers can trust it.
- Render an agent’s findings alongside the supporting telemetry and maintain performance with large datasets.
- Optimize browser performance for demanding data workloads using Web Workers, OPFS-backed caching, and approaches outside React when the framework becomes a bottleneck.
- Contribute to the component library to keep agentic user-interface patterns consistent across the product.
- Collaborate with backend and full-stack engineers on the application programming interface design that powers agent sessions.
- Experience shipping products to users at scale, including large data volumes, significant active user counts, or deep technical complexity.
- Experience shipping large language model-powered features.
- Experience building chat or agentic interfaces with streaming responses, tool-call rendering, or long-running tasks.
- A strong understanding of web performance optimization and browser rendering.
- Experience with modern CSS, including Tailwind, and component libraries such as Radix UI to build design systems.
- Experience using technical visualization tools such as WebGL, D3.js, or Apache ECharts, along with WebAssembly and time-series data.
- Experience building tools for technical users, including dashboards or data-editing environments.
- Experience developing a personal ecosystem of artificial intelligence development tooling, including custom agents, skills, scripts, or workflows.
- A background in scientific computing or hardware test and telemetry.
SiftStack provides automated certification and compliance tools tailored for fast-moving engineering teams. Its platform streamlines the certification process by generating automated reports, capturing institutional knowledge, and documenting data and decisions to speed up investigations and reduce software costs. It includes cloud-spending optimization to keep tools responsive and within budget, and supports easy onboarding so engineers can start in an hour or less. The product also enhances collaboration with advanced teamwork features, and uses real-time rules on a streaming event engine to spot anomalies quickly for fast decision-making. Unified visualization and query-optimized storage enable situational awareness across millions of datasets and time-synchronized logs. SiftStack operates on a subscription model, serving engineering teams across industries to improve compliance workflows and overall productivity.
Company Size
51-200
Company Stage
Series B
Total Funding
$67M
Headquarters
El Segundo, California
Founded
2022
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Simplify's Take
What believers are saying
- June 2026 FedRAMP High certification unlocked federal procurement immediately.
- August 2026 Sift Edge early access targets aerospace, robotics, defense, and energy buyers.
- Management said 2026 raised $67 million and tripled revenue yearly since 2022.
What critics are saying
- Palantir, Anduril, and Applied Intuition already crowd the defense data platform stack.
- Sift's revenue depends on hardware programs; delayed launches and canceled test campaigns hit bookings fast.
- If edge telemetry becomes a cloud feature from Databricks or Snowflake, Sift loses category control.
What makes SIFT unique
- Sift ingests 20 million data points per second across aerospace, defense, autonomy, and manufacturing.
- Sift Edge runs offline on one machine, preserving telemetry during outages and syncing later.
- FedRAMP High certification with Knox opened federal agencies and national security programs.
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Benefits
Remote Work Options
Company Equity
Flexible Work Hours
Growth & Insights and Company News
6 month growth
↑ 2%1 year growth
↑ 3%2 year growth
↑ 20%Sift has launched Sift Edge, a data infrastructure platform designed to capture telemetry in challenging test environments where power and network connections are unreliable. The product runs locally at test sites in aerospace and defence environments, recording measurements continuously even during outages and syncing data to the cloud when connectivity returns. Built as a Rust application for macOS, Windows, and Linux, Edge operates on a single machine without requiring clusters or additional services. It writes streaming telemetry directly to local disk and provides a native desktop app for live data viewing and querying. The platform eliminates the need for separate homegrown systems typically used to manage outages. Teams can control what data syncs to Sift's cloud service, which is particularly useful when test stands generate more data than organisations want to transmit. Sift Edge is available on request for teams in aerospace, defence, robotics, and energy sectors.
Sift achieves FedRAMP High certification through partnership with Knox Systems. PR Newswire Certification Enables Federal Agencies to Adopt a Unified Platform that Captures, Stores, and Automatically Analyzes Sensor Data to Help Engineers Identify Issues Faster MARINA DEL REY, Calif. and NEW YORK, June 2, 2026 /PRNewswire/ - Sift, the data infrastructure platform for physical AI, today announced it has achieved Federal Risk and Authorization Management Program (FedRAMP) High certification in partnership with Knox Systems (Knox), the largest federal AI-managed cloud provider. FedRAMP is a rigorous and exclusive U.S. government program designed to standardize security assessment and authorization for cloud service offerings and accelerate adoption of government-grade cloud solutions by federal agencies. Built by engineers with first-hand understanding of the demands of mission-critical hardware environments, Sift provides the data infrastructure layer that enables both engineers and AI systems to make sense of the massive volumes of sensor data generated by physical machines. With this authorization, federal agencies now have access to a purpose-built platform for hardware sensor data with automated anomaly detection, real-time data review, and long-term data retention across programs. "At Sift, we are committed to giving engineers the infrastructure they need to build, test, and operate more reliable hardware systems," said Austin Spiegel, CEO and Co-Founder of Sift. "Too often, engineering teams generate massive amounts of data but must rely on manual workflows, fragmented tools, and legacy systems that break down at scale. Our FedRAMP certification means that engineers working on national security missions now have access to a unified platform that is already proven at scale. Customers already use Sift inside air-gapped environments to handle millions of concurrent sensors across multiple formats and time scales, for both development and live ops. We're excited to bring these services to federal agencies." Knox eliminated the complexity of the FedRAMP authorization process, allowing Sift to obtain FedRAMP High certification within a matter of months while keeping valuable engineering resources focused on product development. As a result, Sift can expand into national security and defense programs and provide federal agencies with access to a proven data platform to support mission-critical hardware environments. "Knox Systems and Sift are cut from similar cloths - we're both delivering solutions based on the challenges that we experienced first-hand," said Irina Denisenko, CEO of Knox Systems. "After partnering with Knox to obtain FedRAMP High certification, Sift can now help national security customers automatically identify anomalies, root-cause issues, and build faster."
Sift, a data infrastructure platform for physical AI, has named co-founder Austin Spiegel as chief executive officer and opened a second office in San Francisco. Co-founder Karthik Gollapudi will focus on product vision and industry evangelism. The company has added six senior leaders from Meta, Anduril, Applied Intuition, Grafana Labs, SpaceX and Palantir, expanding its team to 80 people. Sift's platform ingests up to 20 million data points per second across aerospace, defence, autonomy, rail and advanced manufacturing programmes. Since 2022, Sift has tripled revenue year over year and raised $67 million in total funding. The platform supports companies including Impulse, K2 Space and Parallel Systems, handling mission-critical systems that must work correctly on first deployment.
Sift raises $42M to build the missing data layer for Physical AI. Sift has raised a $42 million Series B led by StepStone, with participation from GV, Riot Ventures, Fika Ventures, and CIV, bringing total funding to $67 million. The company is targeting a growing gap in AI infrastructure: the ability to make physical machines understandable to AI systems. As AI moves beyond software into real-world environments, systems like rockets, satellites, and autonomous vehicles generate millions of sensor data points per second across audio, video, logs, and telemetry. But unlike software environments, this data is largely unstructured and difficult to interpret. Sift's platform aims to solve this by transforming raw machine data into structured, queryable formats that both engineers and AI models can use. In effect, it acts as an "observability layer" for hardware, bringing a level of visibility that software systems have developed over the past two decades. Founded by former SpaceX engineers, the company is already working with organizations such as ULA, Astranis, and K2 Space, supporting systems that operate at fleet scale rather than as isolated machines. The shift from managing single assets to operating constellations of hundreds or thousands of systems is driving demand for automation in monitoring, anomaly detection, and performance validation. With the new funding, Sift plans to expand its engineering team and platform capabilities as more industries move toward AI-controlled hardware systems across defense, space, manufacturing, and autonomy. TheMarketAI take. TheMarketAI has written before that physical AI is fundamentally different from software AI. Large language models benefit from abundant, structured data. Physical systems do not. Instead, they produce messy, high-frequency, multi-modal data that is difficult to interpret and even harder to scale. Sift is tackling a less visible but critical layer of that problem: making the physical world legible to AI. Before AI can control machines, it needs to understand them. That requires translating raw sensor output into structured data pipelines - something that, until now, has largely been handled manually or through fragmented tools. This reinforces a broader theme in Physical AI: progress may not come from better models alone, but from infrastructure that bridges the gap between real-world complexity and machine understanding. The physical part of AI remains both the hardest and most interesting frontier. Companies like Sift are betting that whoever builds the data layer wins.
Sift, founded by SpaceX veterans, has raised $42 million in a Series B round led by StepStone, with participation from GV, Riot Ventures, Fika Ventures and CIV. The funding brings total capital raised to $67 million. The company provides an intelligence layer that transforms raw sensor data from mission-critical machines into structured, queryable information for engineers and AI systems. Its platform addresses the infrastructure gap between AI capabilities and physical hardware operation across space, defence, manufacturing and autonomy sectors. Sift's clients include ULA, Astranis, K2 Space and Parallel Systems. The company plans to nearly double its workforce from 70 employees and relocate to larger headquarters in Marina Del Rey. CEO Karthik Gollapudi and co-founder Austin Spiegel previously built monitoring systems for rockets and spacecraft at SpaceX.