TechGrove is the Centre of Excellence for Banyan Software, based in Chennai, India. It plays a key role in supporting Banyan’s global businesses through technology, security, and software development. TechGrove brings together India’s deep pool of technical talent with Banyan’s long-term approach to growth, creating a trusted, developer-focused environment where people can do their best work.

About Berkeley Myles

We build software for UK manufacturers who can't afford to get things wrong: aerospace, medical devices, oil and gas, motorsport. Our product, ProgressPlus, runs the whole job from first enquiry through to final invoice. Hundreds of manufacturers run on it every day, and when one of them has to prove what went into a part, it's where the answer comes from. We're now building a new product with

AI on every stage of that flow.

We're part of Banyan Software, the best permanent home for software businesses that serve specialised industries, their employees, and their customers. Banyan is a Great Place to Work Certified company, a five-time Inc. 5000 honoree, and a top-10 company on the Deloitte Technology Fast 500.

Founded in 2016 and headquartered in Atlanta, Banyan operates more than 100 portfolio companies across North America, the UK, the EU, and APAC.

About the Role

ProgressPlus has been running factories since 1999. Every rule inside it is a decision someone once made about how a manufacturer works: when a quote becomes an order, what commits stock, what has to be true before a part can ship. Hundreds of businesses have built their working day on those decisions.

We're building the replacement. Feature by feature, that means understanding why each of those rules exists, building what the product manager decides it should become on a cloud platform with AI on every stage, and speaking up when what you find in the old system changes the answer.

You'll work across the whole flow: enquiry, quote, order, jobs, scheduling, tracking, quality, shipping,

invoice. One month that's purchasing, the next it's shop-floor tracking, and each feature runs from the data model through the .NET service to the part a planner or an inspector uses all day. The features that matter most span several stages, because a change to an order ripples through jobs, stock and invoicing, and the customer expects all of it to agree. That's why every engineer here works across the whole flow.

The platform is built and running: five .NET services on Azure with architecture boundaries enforced in

CI, a database per customer company, and a Next.js frontend. A platform engineer owns that estate and the path to production. An AI engineer owns the agent layer. You build the product on top of both, and canvas once the agent layer exists, you'll be among the first to put AI into the flow. The team you'd join is small:

five engineers and a lead.

We build with AI coding agents, wired into our issue tracking and version control. The repo already holds what they need: project instructions, coding rules per area, specialised agents for tests,

documentation and architecture review, and a learnings log the team maintains. You'll direct the agents,

review what they produce, and answer for everything you merge.

Key Responsibilities The kind of work on the board: an operator books on and off a job from a tablet on the shop floor and the planner's schedule moves before they refresh. A delivery arrives against a purchase order, gets allocated to the jobs waiting on it, and leaves behind the certificate an aerospace customer will ask for a year later. A quantity changes on a sales order and the works orders, material demand and invoice downstream all agree with it.

A stock grid holds every part a customer owns, with filters that compile to





SQL and stay fast. And, once the agent layer lands, the first AI on a stage: an agent that drafts a job's audit pack from its real records, with a person approving every page.

Building the product

Take features end to end across any stage of the flow, from the data model to what the user touches,

with tests at each layer

Get the cross-stage behaviour right: when an order, a job and an invoice have to agree, make sure they do

Get authorisation and validation right on every feature, and never be the reason data crosses between customers

Write schema changes as migrations that run safely across every customer's database

Keep it fast at real volumes: a customer's full parts list, years of jobs, and a shop floor writing to it all day. Instrument it so we can see when it isn't

Prototype when you see a better way. The product manager leads the design and there is no designer in between, so engineers build prototypes against the product's patterns and bring them to the product manager

Build the integrations customers depend on: APIs for the systems that read from ProgressPlus,

connectors into the ones it reads from, and versioning so neither breaks when we change something

Working with agents

Direct coding agents on production work: break work into tasks they can execute reliably, supervise them to a merged and tested result, and intervene when their output is wrong. You know which work to hand an agent and which to do yourself

Maintain the agent context: project instructions, per-area rules, reusable skills, and the learnings log,

so the next person or agent working in that area starts from what you learned The team and the customer

Review others' work across the flow with the same rigour as your own, and take review from them the same way canvas

Take your turn on the application team's support rota: triage what comes in, fix what's yours, and write up anything that should never happen twice

Spend time with the people who use the product, customers and our own support team, and turn what you learn into what gets built

Support UAT and resolve defects before and after release, and build the features customers need before they can move off the legacy product

How We Work

Linear as the single board: work traced from issue to acceptance criteria to PR, reporting as a by-

product of the work A small team: full stack engineers with a lead, plus AI and platform specialists, on a .NET and Next.js platform on Azure

Prototype-led: we design the flow before we build it, against a shared design system

AI in daily use across the team: coding agents in the repo with the context they need, and AI tooling for research, prototyping and analysis A customer base we can pick up the phone to, and an implementation team on their sites every week

Tech Stack You'll Use

Backend: C#, .NET 10, Rebus messaging, SQL Server (database per company), EF Core

Frontend: Next.js, React, TypeScript, TanStack Table, Tailwind

Testing: xUnit, Vitest and Testing Library, Playwright

Cloud: Azure (Container Apps, Azure SQL, Service Bus), GitHub Actions

Tooling: Claude Code, Linear, GitHub

What We're Looking For

5+ years building customer-facing web products across the full stack, and a track record of driving complex, end-to-end features, not incremental improvements, with visible impact on the product





Hands-on experience directing agentic coding tools (Claude Code, Cursor, Copilot agents or equivalent) on production code. You can walk us through specific work you shipped this way, how you structured it, and where you had to step in

Deep enough in C# / .NET and TypeScript / React to know when the code is wrong, whoever wrote it

Solid relational database skills: you can design a schema within an existing model, write a migration you'd run against live data, and find the slow query

You treat tests as part of the definition of done, and you can prove a test works by breaking it on purpose

Product sensibility: you care about UX, speed and polish, you'd rather ask the person using it for eight hours a day than guess, and you push back when something doesn't feel right canvas

High ownership: a self-directed, full-lifecycle builder who takes a feature from a conversation with a user to production, and helps shape the problem rather than waiting for a spec

Comfortable in a large product you didn't build: you read before you write, you find the existing pattern before inventing one, and you know when to ask for a second opinion

You can explain a technical decision and its trade-offs to someone who doesn't write code, and change your mind when they're right

Solid written communication: you'll work with a team split across time zones

This isn't the role if you want a finished spec before you start, if you'd rather stay on one side of the stack, if you see coding agents as either a threat or a toy, or if a product with twenty-five years of customers behind it sounds like baggage rather than material.

Preferred Experience

Manufacturing, ERP, MRP or supply chain systems, or genuine curiosity about how factories run

Multi-tenant SaaS, especially database-per-tenant

Azure services and cloud-hosted applications

Building product features on top of an internal agent or tool layer

Authoring agent skills, prompt libraries or project instructions that other engineers relied on

Accessibility (WCAG) and offline-first or PWA work for the shop floor

Replacing a system people already depend on, where "how it works today" is both the spec and the problem

What We Offer A team that builds with agents as standard, and a repo that already carries the context they need

What you ship goes into factories that can't run without it The backing of Banyan Software, a permanent home for software businesses, with the pace of a small product team

Pension, holiday entitlement, remote working and a learning budget A direct line into product and architecture decisions

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📌 Fullstack Engineer (Bengaluru)
🏢 TechGrove by Banyan Software
📍 Bengaluru