We are looking for an Business & Operations Engineer who can understand our business and operations and use AI, automation, engineering, and data to make the company work better.
Our processes are currently spread across different teams, applications, spreadsheets, CRMs, and manual workflows. We need someone who can understand how these processes work, identify what is inefficient or fragmented, and then build, test, deploy, and maintain reliable systems that connect, automate, and improve them.
This is a highly hands-on role. You will work closely with the business, understand operational requirements, design solutions, build them, test them against real-world scenarios, deploy them, maintain them, and measure their impact.
The ideal candidate is someone who can move comfortably between business operations, data, AI, automation, integrations, software development, and production support.
What You Will Do Business Operations & Process Improvement
- Understand the company's business operations, workflows, and processes across different teams.
- Work directly with teams and management to understand their requirements, problems, and bottlenecks.
- Identify repetitive, manual, inefficient, and fragmented processes.
- Translate business processes and requirements into practical technology and automation solutions.
- Continuously identify opportunities to improve the company's operations through technology.
- Determine which processes should remain manual, which should be automated, and which can be redesigned around AI.
- Take ownership of improving operational systems rather than simply documenting problems.
AI & Intelligent Automation
- Identify opportunities where AI and automation can create meaningful improvements in the business.
- Design, prototype, test, and productionize AI-powered and agentic workflows.
- Integrate workflows with AI platforms and LLM services.
- Build AI workflows capable of handling complex, variable, or unstructured information.
- Use AI for classification, extraction, summarization, decision support, intelligent routing, process execution, and exception handling.
- Evaluate existing automation approaches and determine where they should be enhanced, redesigned, or replaced with AI-native or agentic solutions.
- Compare different approaches using measurable outcomes such as accuracy, reliability, time saved, cost, and business impact.
Automation, APIs & Integrations
- Build, deploy, and maintain business process automations.
- Integrate applications and systems using APIs, webhooks, browser-based workflows, and custom code.
- Build workflows using tools such as n8n, Zapier, and similar platforms.
- Maintain existing automation solutions by diagnosing failures and fixing issues.
- Adapt automations when dependent applications, websites, APIs, or business processes change.
- Ensure deployed automations remain reliable for the teams that depend on them.
- Build appropriate error handling, logging, monitoring, alerts, and recovery mechanisms into production workflows.
- Maintain clear documentation, version control, testing procedures, and change-management practices.
- Establish reusable engineering patterns and standards for automation architecture, code quality, deployment, and support.
- Monitor automation performance, including execution volumes, errors, reliability, processing time, and time saved.
Application Development, Testing & Production Reliability
- Build internal tools, dashboards, web applications, interfaces, scripts, and other solutions when existing software is not sufficient.
- Use Claude Code, Codex, and other AI-assisted coding tools to rapidly turn business requirements into working solutions.
- Be comfortable with rapid development or "vibe coding", while understanding that producing a working prototype is only the beginning.
- Take responsibility for thoroughly testing everything you build before and after deployment.
- Test individual features, workflows, integrations, data flows, permissions, inputs, outputs, and failure scenarios.
- Think through real-world production scenarios rather than testing only the expected or "happy path."
- Test for incorrect or unexpected inputs, missing data, duplicate records, API failures, timeouts, system changes, partial failures, user errors, and other edge cases.
- Validate that applications and automations continue to work reliably under the conditions they will encounter in actual business operations.
- Monitor systems after deployment and proactively identify and fix reliability issues.
- Maintain and improve applications as business requirements and dependent systems change.
- Turn successful prototypes into stable, maintainable, production-ready systems.
Web development in this role is not simply about building applications or prototypes. We expect the person to have enough engineering experience to test what they build thoroughly, think through individual real-life use cases and edge cases, identify failure modes, and ensure the application is reliable in a production environment.
CRM & Business Systems
- Take ownership of the company's CRM and continuously improve it.
- Maintain clean, structured, accurate, and reliable CRM data.
- Build CRM workflows, pipelines, automations, and processes based on business requirements.
- Integrate the CRM with other applications and systems.
- Identify opportunities to improve how teams use the CRM and how information flows through the business.
- Build or customize CRM functionality when existing capabilities are not sufficient.
Data & Business Intelligence
- Bring together data from different systems and make it useful for decision-making.
- Analyze operational, sales, customer, marketing, financial, and other business data.
- Build dashboards, reports, KPIs, and business intelligence tools.
- Provide clear and actionable insights rather than simply presenting data.
- Help management understand what is happening across the business.
- Identify trends, bottlenecks, opportunities, anomalies, and areas for improvement.
- Measure the impact of automation and operational changes using data.
- Work extensively with Excel / Google Sheets, SQL, databases, and other data-analysis tools.
What We're Looking For
We are looking for someone who combines strong business understanding with strong technical and engineering ability.
You should be able to sit with someone from the business, understand what they are doing and why, identify the underlying problem, and then figure out how technology can solve it.
You don't need to know every tool we use. What matters is that you can learn quickly, figure things out independently, build solutions, and take responsibility for making sure those solutions actually work in production.
You should have experience with several of the following:
- Business operations and process improvement
- AI and workflow automation
- APIs, webhooks, and system integrations
- Browser-based automation
- n8n, Zapier, or similar automation platforms
- CRM systems
- LLM and AI platform integrations
- Agentic AI workflows
- Claude Code, Codex, or similar AI coding tools
- Rapid prototyping / vibe coding
- Application testing and production deployment
- Debugging and troubleshooting
- Python, JavaScript, or another programming language
- Web development
- SQL and databases
- Excel / Google Sheets and data analysis
- Dashboards and data visualization
- Git / version control
- Logging, monitoring, alerting, and production support
The Kind of Person We Want
We want someone who naturally asks:
"Why are we doing this manually?"
"Why aren't these systems connected?"
"Can we automate this?"
"Can AI handle this?"
"What happens when something goes wrong?"
"Have we tested all the real-world cases?"
"How do we know this will actually work in production?"
You should enjoy taking messy, real-world business problems and turning them into simple, reliable, measurable systems.
You should be comfortable moving from:
Business problem → Understand the process → Analyze the data → Design the solution → Build → Test → Deploy → Monitor → Improve
You should also understand that building the solution is only part of the job. Testing, reliability, maintenance, monitoring, and continuous improvement are equally important.
What Success Looks Like
When a team tells you, "We spend three hours every day doing this manually," you should be able to understand the process, determine what can be automated, build the solution, test it against real-world scenarios, deploy it, monitor it, and measure the time saved.
When an automation breaks, you should be able to diagnose the failure, fix it, understand why it happened, and make the workflow more resilient.
When two systems don't communicate, you should be able to figure out how to connect them.
When management asks, "What's happening with this part of the business?", you should be able to find the data, analyze it, and provide a clear answer.
When someone says, "Wouldn't it be great if we had a tool that did this?", you should be able to rapidly build a prototype, test it with actual users and real scenarios, improve it, and turn it into a reliable production system if it creates value.
Ultimately, we are looking for someone who can understand the business, identify opportunities, build the technology to solve them, and take responsibility for ensuring what they build works reliably in the real world.
Pay: ₹613,944.07 - ₹978,377.83 per year
Benefits:
- Cell phone reimbursement
- Commuter assistance
- Flexible schedule
- Food provided
- Paid sick time
- Paid time off
- Provident Fund
Work Location: In person
