Senior Software Engineer, Full Stack (Agentic AI)

We Love AI Jobs; Northern (KY); Hybrid; USD 180,000 - 230,000; Full time

Job summary

Sift is seeking a senior software engineer to build Sift Agents, frontend, APIs, and agent infrastructure for reliable scale. You will translate customer needs into MVP and beyond, shaping product iterations from initial release through subsequent updates.

You will own major components across the stack, from frontend micro-interactions to Kubernetes orchestration, working closely with customers and cross-functional teams to ship high-impact features that improve latency, cost, and reliability.

Qualifications

• 8+ years of professional software engineering experience.
• Frontend web applications built with React/NextJS.
• APIs or backend services built with Go, Python, or Rust (REST, gRPC).
• Curiosity about new AI products and driving product-facing improvements.

Responsibilities

• Talk directly to customers and partner with product to turn workflows into agent capabilities.
• Design, ship, and operate agentic systems that reason over large-scale time-series data and hardware context.
• Build frontend surfaces and APIs for Sift Agents with reliable UX.
• Develop and maintain MCP server to query telemetry for agents and tools.
• Run agents reliably at scale in cloud and on-prem environments.
• Create evaluation suites to measure quality, latency, cost, and failure modes in production.
• Integrate and assess frontier models across providers.

Skills

React

NextJS

TypeScript

Go

Python

Rust

Kubernetes

MCP

Tools

REST

gRPC

Job description

Sift builds telemetry analysis software for hardware engineering teams, and this role works across the stack on Sift Agents, which investigate anomalies and answer questions about test and flight data. You’ll partner with customers to shape the product and build its frontend, APIs, and agent infrastructure for reliable use at scale.* Permanent* Hybrid* 8+ years### Skills and expertiseReactNextJSTypeScriptGoPythonRustKubernetesMCP### Key responsibilities* Translate customer review workflows into agent features and own product iterations from MVP onward.* Build frontend experiences, APIs, and supporting systems for Sift Agents.* Evaluate agent usefulness and monitor quality, latency, cost, and failures in production.## How this job comparesCompared with 1,635 open senior engineering jobs on October 10, 2026.Pay: This job pays $180K to $230K a year. The 719 open senior engineering jobs that publish US pay start at $164K on average, so this job starts about 10% higher.Similar open jobs: We Love AI Jobs lists 1,635 open senior engineering jobs at 344 companies.Remote work: This job is hybrid. 271 of the 1,635 senior engineering jobs (17%) are remote.AI in this role: High. AI is the core of the work: building, training or deploying AI systems. The role builds the Sift Agents product and its supporting tools, execution systems, and evaluations. It also integrates and assesses frontier models across providers.## Full descriptionAbout SiftSift is the data infrastructure platform for hardware engineering teams. Sift turns high-frequency telemetry into engineering insights for mission-critical systems. Teams use Sift to build and operate rockets, satellites, autonomous vehicles, energy systems, defense platforms, and more.Founded by former SpaceX engineers who built the tools behind Dragon and Starlink, Sift is building the data infrastructure to herald the AI era for physical systems.About the RoleHardware 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 frontend micro-interactions that make the chat experience feel great, the next you might be writing the Kubernetes scaling logic that orchestrates agent workloads. 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 dependable: tool design, context management, code execution environments, evaluation, and observability.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• Design, ship, and operate agentic systems that reason over large-scale time-series data and hardware domain context• Build everything around the model that makes agents dependable: tool interfaces, sandboxed execution for agent-generated code, context and memory management, custom compaction algorithms, opinionated skills, and guardrails• Develop and maintain Sift’s MCP server, the tool surface that lets both our agents and our customers’ AI tools query telemetry directly• Work across the whole stack• Build the frontend surfaces where Sift Agents live, and make them feel great• Design and implement the APIs that power our agentic capabilities• Run agents reliably at scale, both in the cloud and on-prem• Build evaluation suites that measure whether agents actually help engineers, and instrument quality, latency, cost, and failure modes in production• Integrate and assess frontier models across providersThe Skillset You'll Bring:• Have 8+ 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 frontend web applications with technologies like React, NextJS, or similar• Have built APIs (REST, gRPC, etc.) or backend services with technologies like Go, Python, Rust, or similar• Are curious about new AI products: you try new agents, models, and features as they ship, and have opinions about what makes them goodIf 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 agentic systems: multi-step tool use, planning loops, context management, and evals• Designed tool ecosystems for agents, including MCP