Freehand Logo

Freehand

Backend Engineer India/US

Reposted 24 Days Ago
Remote
Hiring Remotely in United States
Mid level
Remote
Hiring Remotely in United States
Mid level
Build and scale backend services and orchestration for AI agents managing procure-to-pay workflows. Implement APIs, integrations with ERPs and payment systems, observability, auditability, secure data pipelines, and testing/eval frameworks to ensure reliable, compliant AI-driven operations at enterprise scale.
The summary above was generated by AI
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

•Strong experience building production backend systems

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

•Deep understanding of distributed systems, APIs and microservices, databases (SQL and NoSQL), and message queues / event-driven architectures

System Design

•Proven experience designing scalable, fault-tolerant systems

•Strong grasp of consistency, concurrency, and data integrity trade-offs

•Experience building workflow engines or state-driven systems is a plus


Enterprise & Data Context

•Experience working with financial systems, enterprise SaaS platforms, or sensitive/regulated data

•Comfort operating in environments where backend failures have a real business impact


Bonus (Nice to Have)

•Experience with multi-agent orchestration and agent-to-agent communication protocols

•Familiarity with event sourcing, rule engines, or policy systems

•Knowledge of production debugging at scale and observability tooling

•Contributions to or experience with open-source LLM tooling ecosystems

•Experience with agent observability tooling (LangSmith, Arize, Helicone, or custom trace pipelines) and eval design

•Experience building LLM-powered systems in production; familiarity with agent frameworks (LangChain, CrewAI, or custom)


Working at Freehand

Series C, ~100 people across the US and India. Big enough to have infrastructure, small enough that your work is visible. We run on five core operating principles; these are not values-on-a-wall, this is the exact philosophy we built our AI agents on :

  • Context Before Confidence. We get in, ask (a ton of) questions, connect the dots ourselves and move fast. No passengers, no hand-holding. The amount of confidence you'll have in Week 1 is directly proportional to the context strive to gain.

  • Decisions, not Recommendations. Freehand folks decide, they don't present options. You'll have real autonomy, and real accountability to match.

  • High Agency, High Trust. We won't manage you closely or ask you to escalate every call. Act, share your reasoning, and course-correct when needed. That's the contract.

  • Accountability is the Product. When something goes wrong — and it will — we name it, learn from it, and move on. No politics, no cover. Just fix it.

  • The Work That Remains is the Work That Matters. We actively cut low-value work. What lands on your plate is there because it matters — and can only be done by you.

It's a small world. Freehand employees Work Anywhere across US & India (we're remote & travel-first). As and when required, for this role, we will also arrange for a fully-paid trip to our HQ in Chennai to meet & interact with cross-functional teams.

In addition, we proudly offer the following Benefits to all our full-time employees:

  • Full Health coverage (accidental, life, vision, dental & health consultations)

  • Monthly home-internet costs

  • Flexible working hours

  • Complimentary food & snacks at the Chennai HQ

Equal Opportunity

Freehand hires on merit — your thinking, your track record, your potential — without regard to race, gender, age, religion, sexual orientation, national origin, disability, or any other protected characteristic. If you meet most of the criteria above but not all of it, apply anyway. We care more about your willingness to learn & take initiative than whether your resume maps perfectly to every line.

 

Similar Jobs

2 Hours Ago
Remote or Hybrid
Expert/Leader
Expert/Leader
Big Data • Food • Hardware • Machine Learning • Retail • Automation • Manufacturing
Develop and maintain statistical and ML forecasting models for SKU-level demand using Python/PySpark and Databricks; analyze model performance (MAPE/bias), post-process outputs, collaborate with demand planners for explainability, produce dashboards and KPIs, and drive continuous improvement in forecasting and data models.
Top Skills: DatabricksGoogle AdwordsGoogle AnalyticsGoogle Cloud PlatformGoogle Tag ManagerJuliaExcelPower BIPysparkPythonRSASSQLTableau
2 Hours Ago
Easy Apply
Remote
Easy Apply
7M-7M Annually
Senior level
7M-7M Annually
Senior level
Artificial Intelligence • Blockchain • Fintech • Financial Services • Cryptocurrency • NFT • Web3
Lead the Help Center product roadmap to increase automation rate and CSAT by building AI-powered search, personalized article experiences, and self-service workflows. Partner with ML, engineering, CX ops, content, and data science to maintain global knowledge, define funnel metrics, and integrate chat/agent tooling and third-party vendors to deflect contacts and proactively resolve issues.
Top Skills: Ai/MlCmsContentfulFreshdeskGenerative AiLlmRagSalesforceZendesk
2 Hours Ago
In-Office or Remote
Senior level
Senior level
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Manage a portfolio of mid-market customers in India: develop and execute account/territory plans, identify and qualify opportunities, expand usage and cross-sell, run demos, build strong client relationships, coordinate internal teams and channel partners, report progress, provide product feedback, and travel occasionally for client and team events.
Top Skills: ConfluenceCRMJira Service ManagementJira Software

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account