
51 - 200 employees
Founded 2026
š¦ Logistics
š¤ Artificial Intelligence
š¢ Enterprise
Logistics ⢠Artificial Intelligence ⢠Enterprise
Freehand is a B2B enterprise software company that uses AI-driven teams and agents to audit freight invoices, enforce logistics contracts, manage supply chain spend, and close disputes with auditable outcomes posted back to customers' ERPs. The company offers freight audit & payment, 3PL contract enforcement, global trade validation (duties/tariffs/FTA benefits) and claims to recover 5ā10% of spend for customers. Freehand raised a $55M Series B to launch AI agents for billing and collections and targets logistics, manufacturing, and retail enterprises.
š„ 0 minutes ago
š United States, India ā Remote
ā° Full Time
š” Mid-level
š Senior
š Backend Engineer
š» Ghost score 12%
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51 - 200 employees
Founded 2026
š¦ Logistics
š¤ Artificial Intelligence
š¢ Enterprise
Logistics ⢠Artificial Intelligence ⢠Enterprise
Freehand is a B2B enterprise software company that uses AI-driven teams and agents to audit freight invoices, enforce logistics contracts, manage supply chain spend, and close disputes with auditable outcomes posted back to customers' ERPs. The company offers freight audit & payment, 3PL contract enforcement, global trade validation (duties/tariffs/FTA benefits) and claims to recover 5ā10% of spend for customers. Freehand raised a $55M Series B to launch AI agents for billing and collections and targets logistics, manufacturing, and retail enterprises.
⢠Build high-throughput, low-latency backend services powering AI agent execution ⢠Develop workflow orchestration systems for complex, multi-step enterprise processes ⢠Implement rule engines and policy enforcement layers for enterprise compliance ⢠Build APIs and integrations with ERPs, procurement tools, payment rails, and data providers ⢠Develop observability, audit, and traceability systems for AI-driven decisions ⢠Build secure data pipelines handling sensitive financial and operational data ⢠Create agent execution runtimes, multi-agent coordination, and observability pipelines ⢠Develop evaluation frameworks and automated test harnesses for agent reliability and output quality ⢠Design and build scalable backend services using modern system design principles ⢠Own services managing procurement, invoice, contract, and payment workflows ⢠Implement orchestration coordinating AI agents, humans, and enterprise systems ⢠Build resilient systems with idempotency, retries, and failure handling ⢠Maintain APIs consumed by AI services, frontend applications, and external systems ⢠Normalize and transform complex data across enterprise systems ⢠Instrument agent execution with trace capture, including tool calls, LLM I/O, latency, token usage, and cost ⢠Define and track agent reliability metrics ⢠Design enterprise-grade monitoring, alerting, access controls, audit logs, and data security ⢠Ensure compliance for financial and regulated data ⢠Optimize latency, throughput, and cost efficiency ⢠Design services scaling across global customers and billions of transactions ⢠Identify and fix distributed-systems bottlenecks
⢠Strong experience building production backend systems ⢠Strong proficiency in Python, NodeJS, Go, or similar backend languages ⢠Deep understanding of distributed systems, APIs and microservices, SQL and NoSQL databases, and message queues/event-driven architectures ⢠Proven experience designing scalable, fault-tolerant systems ⢠Strong grasp of consistency, concurrency, and data integrity trade-offs ⢠Experience working with financial systems, enterprise SaaS platforms, or sensitive/regulated data ⢠Comfort operating where backend failures have real business impact ⢠Experience with workflow engines or state-driven systems is a plus ⢠Experience with multi-agent orchestration and agent-to-agent communication protocols is nice to have ⢠Familiarity with event sourcing, rule engines, or policy systems is nice to have ⢠Knowledge of production debugging at scale and observability tooling is nice to have ⢠Contributions to or experience with open-source LLM tooling ecosystems is nice to have ⢠Experience with agent observability tooling and evaluation design is nice to have ⢠Experience building LLM-powered systems in production and familiarity with agent frameworks is nice to have
⢠Work Anywhere across the US & India ⢠Remote and travel-first work arrangement ⢠Fully-paid trips to the HQ in Chennai as required ⢠Opportunity to meet and interact with cross-functional teams ⢠High autonomy and accountability ⢠Visible work in a Series C company of approximately 100 people ⢠Professional growth through learning and taking initiative
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