Backend Engineer for AI Agents & Time-Series Systems

Sift; California (MO); Hybrid; USD 150,000 - 200,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

Sift, based in Marina Del Rey, CA, seeks a product‑oriented software engineer to own AI agent tooling for hardware telemetry. You will engage with customers to define features and guide them from MVP to production across cloud and on‑prem environments.

You will design and ship scalable agentic systems, build robust tool interfaces, and ensure observability and reliability in time‑series data workflows. Join a fast‑moving team shaping the AI era of physical systems.

Qualifications

• 3+ years of professional software engineering experience.
• Own a product area by talking to customers, deciding what to build, and shipping.
• Built APIs (REST, gRPC) and backend services with Go, Python, Rust or similar.
• Working knowledge of distributed systems fundamentals.
• Curious about new AI products and features as they ship.

Responsibilities

• Talk directly to customers and partner with product to turn workflows into agent capabilities.
• Design, ship, and operate agentic systems that reason over time-series data and context.
• Build tool interfaces, sandboxed execution, memory management, and guardrails for agents.
• Develop distributed systems to support long-running agent workloads on Kubernetes, cloud and on-prem.
• Design and implement APIs powering agentic capabilities.
• Build evaluation suites to measure impact, latency, cost, and reliability in production.
• Integrate frontier models across providers.

Skills

APIs (REST)

gRPC

Go

Python

Rust

Distributed systems

Customer focus

AI products

Tools

Go

Python

Rust

REST

gRPC

Job description

Sift, based in Marina Del Rey, CA, seeks a product‑oriented software engineer to own AI agent tooling for hardware telemetry. You will engage with customers to define features and guide them from MVP to production across cloud and on‑prem environments.

You will design and ship scalable agentic systems, build robust tool interfaces, and ensure observability and reliability in time‑series data workflows. Join a fast‑moving team shaping the AI era of physical systems.