Software Engineer, Business Systems

Function: Business Technology & Security — Business Systems 

Location: Pune, India · Hybrid

Reports to: Product Manager, Business Systems

Experience: 2–4 years

Build and run the integrations, pipelines, automations and internal tools that connect Mindtickle's business systems — Salesforce, NetSuite, HRMS, Slack and Google Cloud. You take defined requirements and own the technical path end to end: design, build, ship, and keep it running.

Business Technology & Security runs the systems, automation and security behind how Mindtickle operates. Business Systems is its build engine — the team that turns requirements from GTM, Finance, People Success, IT, Legal and Security into shipped systems: integrations, data pipelines, automations, internal tools and agents.

We are a small team. You will not be part of a traditional engineering squad with sprints and Scrum ceremonies. You will operate independently, usually owning a problem from a defined requirement through to a deployed, monitored solution — and then continuing to own it.

You are the engineer on the team. When a system needs to talk to another system, when a manual process needs to become an automated one, when a tool needs to exist and doesn't — you build it.

Requirements come to you defined. The Product Manager and Business Systems Analyst own the business problem, the stakeholders, and the question of whether we should do it at all. The technical path is entirely yours — how it's designed, what it's built on, how it's tested, how it fails safely, and how it's supported once it's live.

Building — about half your time Integrations between business systems. Data pipelines. Automations that remove manual work from Finance, People Success, IT, Security and GTM. Internal tools and lightweight services. AI-backed workflows and agents where they are the right answer, and conventional code where they are not.

Running it — about a fifth of your time You inherit a set of automations already in production and become their owner. Monitoring, alerting, incident response, and the unglamorous work of making inherited systems observable and documented. Nothing you build gets handed to someone else to support.

Technical evaluation — about 15% When the team is deciding whether to build or buy, or whether a vendor's API can actually do what the demo claimed, you build the prototype that answers it. Deep technical spikes, integration feasibility, and performance and security reality-checks — against a requirement the Product Manager and Analyst have already defined.

Migrations — about 15% Data migration, field mapping, cutover scripts and system replacements as we move platforms.

Daily — Writing Python with Claude Code. Reading vendor API documentation. Wiring REST and GraphQL APIs, webhooks and event-driven flows. Debugging a sync that silently dropped records. Deploying to Cloud Run.

Weekly — Shipping an increment and demoing it. Working through requirements with the Product Manager and Analyst. Triaging what broke.

Monthly — One meaningful capability live in production, with monitoring, a runbook, and documentation good enough that someone else could pick it up.

Python · Google Apps Script · Google Cloud Platform (Cloud Run, Cloud Functions, Cloud Scheduler, Pub/Sub, BigQuery, Firestore, Cloud Storage, Compute Engine) · REST and GraphQL APIs, webhooks, OAuth and service-account authentication · Claude Code and modern AI tooling as a primary way of working · Git and CI/CD

Business systems you will integrate with: Salesforce, NetSuite, HRMS, Slack, Google Workspace, and the wider SaaS estate.

We care about what you have built and kept alive, not the tools listed on your CV.

• 2–4 years building software, integrations or automations in a professional environment

• Strong Python, and real fluency with APIs — authentication, rate limits, retries, idempotency, pagination, webhooks and event-driven patterns

• You have built integrations against SaaS APIs, not only configured them through consoles or drag-and-drop integration platforms

• Hands-on cloud experience (GCP preferred; AWS or Azure is fine) with a working understanding of how to compose services rather than follow a tutorial

• End-to-end ownership you can point to — a system you designed, built, shipped and then operated. Something that broke in production and you fixed it.

• Debugging across system boundaries — when two systems disagree about the same record, you can work out why

• Testing and verification instinct — you know your output is correct because you measured it, not because it ran without erroring

• Fast on unfamiliar ground — you have picked up a stack you didn't know and shipped it. This matters more to us than prior exposure to any specific technology.

• Clear written communication — design notes, runbooks, and documentation are part of the job, not an afterthought

• Building AI agents, tool-use, and agentic workflows; MCP servers

• Exposure to business systems — CRM, ERP, HRIS, ITSM — and the SaaS ecosystem around them

• Data and pipeline work (BigQuery, ETL/ELT)

• Infrastructure-as-code