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Freehand

Backend Engineer (USA)

United StatesRemote · United States
FullTime · Engineering
POSTED 27 AUGVERIFIED 1D AGO
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Role
74 days opentrue age
Posted 27 Aug
Payats field
$150k–300kposted
▲ +15% vs market median $195k
$150k$300k
Market p25–p75
$163k–$230k
United States · n=285 · 365d to 6 Nov
CompanyFreehand →
10open roles
Opened · 30d
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Closed · 30d
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3d of snapshots · 30d window
Market
3,489open · Backend
Opened · 7d
+1595% of open
All backend
8,379open
All tracked boards · live 10 Nov · n=3,489
Node.jsPythonGoRuby/RailsLLMsDistributed systems

About Freehand

Most AI companies are building tools. We're building the worker.

Freehand's AI agents replace the human decision-making and coordination layer that sits above enterprise software — handling the analysis, negotiation, prioritization, and execution that previously required armies of logisticians / supply chain professionals.

Our customers include Apple, Meta, GE, Pfizer, J&J, Schlumberger, Cardinal Health, and Unilever. They chose us because we have a fundamentally different answer to what enterprise software looks like when AI can do the job.

If you want to work on something that matters, with people who will push you to be sharper than you thought you could be, this is the place.

The Role & The Team

As a Backend Engineer at Freehand, you will build the distributed systems, APIs, and AI agent infrastructure that power AI-driven enterprise execution. You will design and scale backend services that orchestrate agents, enforce business rules, integrate deeply with ERPs and financial systems, and ensure that every action taken by AI is secure, traceable, and reliable.

This is not CRUD SaaS work. You will be building the backend for autonomous systems handling real money and real risk—and the observability and testing infrastructure to keep those systems trustworthy at scale.

What You'll Do

•High-throughput, low-latency backend services that power AI agent execution

•Workflow orchestration systems for complex, multi-step enterprise processes

•Rule engines and policy enforcement layers for enterprise compliance

•APIs and integrations with ERPs, procurement tools, payment rails, and data providers

•Observability, audit, and traceability systems for AI-driven decisions

•Secure data pipelines handling sensitive financial and operational data

•Agent execution runtimes, multi-agent coordination, and observability pipelines for AI-driven workflows

•Evaluation and testing harnesses to validate agent behaviour, reliability, and output quality

Key Responsibilities

Backend & Systems Engineering

•Design and build scalable backend services using modern system design principles

•Own critical services that manage procurement, invoice, contract, and payment workflows

•Implement orchestration logic that coordinates AI agents, humans, and enterprise systems

•Build resilient systems with strong guarantees around idempotency, retries, and failure handling

API & Integration Development

•Build and maintain robust APIs consumed by AI services, frontend apps, and external systems

•Integrate deeply with ERP systems, procurement platforms, and payment gateways and financial rails

•Handle complex data normalisation and transformation across enterprise systems

AI Agent Building, Observability & Testing

•Build agent execution runtimes: tool calling, context management, memory, and multi-step reasoning loops

•Implement multi-agent coordination—parallel and sequential workflows with human-in-the-loop escalation

•Instrument agent execution with full trace capture: tool calls, LLM I/O, latency, token usage, and cost

•Design evaluation frameworks for agent output quality, task success rate, and regression detection

•Build automated test harnesses for agent pipelines—unit, integration, and replay-based regression tests

•Define and track agent reliability metrics: task completion rate, escalation rate, cost per workflow, and SLA adherence

Reliability, Security & Compliance

•Design systems with enterprise-grade reliability, monitoring, and alerting

•Implement fine-grained access controls, audit logs, and data security best practices

•Ensure backend systems meet compliance requirements for financial and regulated data

Performance & Scale

•Optimize backend systems for latency, throughput, and cost efficiency

•Design services that scale across global customers and billions of transactions

•Proactively identify and fix bottlenecks in distributed systems

Required Skills & Experience

Core Backend Skills

•6-15 years experience building strong production backend systems

•Strong proficiency in Python, NodeJS, Go, or similar backend languages

Source · FreehandFirst seen 2 NovOriginal ↗