VBA Developer

About the role 

Most QA teams test software. We want someone who builds a machine that gets better at testing software every time it encounters a bug. 

This is not a role for someone who "uses AI tools." This is a role for someone who thinks like an architect. You will design a QA system that is legible to machines — structured, documented, and self-improving — so that the knowledge of every bug ever found is permanently encoded, queryable, and feeds back into the next test cycle. The goal is simple: the longer you are here, the harder it should be for us to ship a bug. 

You will own quality for Cash, a digital lending app (short-term personal loans) on Android and web — and that ownership extends from the front end all the way through to the back end. 

You are the first QA hire. You will build this function from scratch. 

There is no existing QA process today. No tooling is chosen. No taxonomy exists. No team is in place. You are the founding hire for this function.

Your first 60 to 90 days will be spent laying the foundation: choosing the tools, defining the bug taxonomy, writing the first skills, and establishing what "done" means across the engineering org. Once that foundation is stable, you will define the team structure you need, propose it, and then lead the hiring yourself. The engineers who join QA after you will be hired because you decided you needed them. 

This is a founder-mode role inside an engineering team. It requires someone who is energised by a blank canvas, not someone who wants to inherit a mature process. 

If you have spent your career executing inside an established QA function and are looking for more of the same, this is not the right role. If you have wanted the mandate to build the system properly from day one and have never had it — this is that opportunity. 

What you will own 

The knowledge base 

Every bug you find — whether in QA or in production — gets documented in a structured, machine-readable format. Not just "what broke" but: what flow triggered it, what the borrower context was, what data state preceded it, what the expected behaviour was, what the actual behaviour was, and which class of error it belongs to. Over time, this becomes Cash's QA Wikipedia — a corpus that an LLM can read and use to generate new test cases, that a new engineer can query to understand failure patterns, and that you can analyse to find where the product keeps breaking. 

This is not documentation for its own sake. It is infrastructure. The test suite is only as good as the knowledge base behind it. 

Skills, not scripts 

For every recurring testing workflow — new feature regression, release smoke test, critical-path sanity check, payment flow validation — you will build a skill: a reusable,

prompt-able test protocol that is AI-executable. When a new engineer joins, they run the skill. When an AI agent is asked to help test a release, it reads the skill. The skill improves every time a bug gets through it. 

The feedback loop 

Every production issue must close the loop. When a bug is found in production, you trace back why the QA cycle did not catch it, update the relevant skill, and add the scenario to the knowledge base. No bug should be found in production twice for the same underlying reason. 

Coverage — front end and back end 

Front end (Android and web) 

● Onboarding and Know Your Customer — Aadhaar/PAN flows, video KYC, bureau pulls 

● Loan application and eligibility decisions — rule engine outcomes, edge cases across credit tiers 

● Disbursement — payment gateway integration, failure states, retry logic

● Repayment — in-app payments, auto-debit, partial payment handling

● Collections and dunning — overdue flows, notification logic, settlement scenarios

● Regulatory compliance — Reserve Bank of India guidelines on digital lending, fair practices code, key fact statement display 

● Cross-platform consistency — Android app and web admin panel 

Back end 

● API contract testing — request/response behaviour, error codes, edge-case inputs

● Rule engine validation — confirming that credit decisioning, eligibility, and pricing logic produces correct outputs for known borrower profiles, including boundary cases

● Data integrity checks — verifying that the right records are created, updated, or flagged after key events (disbursement, repayment, status transitions)

● Integration testing — bureau, KYC provider, payment gateway, and notification service behave correctly end-to-end 

● Regression on back-end changes — any service update, migration, or config change must pass a defined back-end test protocol before reaching production 

Failure-state and idempotency testing 

Disbursements and repayments involve real money. What happens if the payment gateway times out mid-disbursement? What happens if a repayment webhook is delivered twice? What happens when a bureau call fails mid-application? You will own failure-path and retry-logic testing explicitly — not as an edge case, but as a first-class part of every release cycle. 

Audit trail and logging validation 

Every significant event in the borrower lifecycle — application submitted, bureau pulled, decision made, loan disbursed, repayment received — must produce a correct, complete, and tamper-evident audit log. You will test that these logs are accurate. In a regulatory inquiry or a borrower dispute, the audit trail is the evidence. 

Security testing (functional) 

You will own a security testing checklist covering: whether borrower data is exposed in API responses or logs, whether sessions expire correctly, whether API responses are correctly scoped to the authenticated user, and whether error messages leak sensitive information. This is not a penetration testing mandate — that is a separate engagement — but functional security hygiene is part of every release. 

Notification and communication testing 

sends SMS, push notifications, and WhatsApp messages at specific borrower lifecycle triggers. You will test correct trigger conditions, correct content, correct recipient,

and correct timing — including the case where the same event should not produce duplicate messages. 

Performance and load testing 

You will own a baseline load test that runs before major releases — simulating concurrent loan applications, concurrent repayments, and peak traffic scenarios. A lending app that degrades under campaign load is a trust problem, not just a technical one. 

Feature flag and staged rollout validation 

Cash introduces features to specific segments (by tier, cohort, or geography), you will verify that flags work correctly — users outside the target segment do not see the feature, and partial rollouts do not produce inconsistent back-end states. 

What good looks like in 90 days 

● Tooling chosen and set up: test management, bug tracking, and at least basic CI/CD integration 

● A structured bug taxonomy with at least five top-level failure classes, each with sub-types and historical examples 

● A skills library covering the five highest-risk flows (loan application, disbursement, repayment, KYC, collections) 

● Every production bug from the past three months documented in the knowledge base with root cause and skill update 

● A release checklist — covering both front end and back end — that an AI agent can execute the first 80% of independently 

What good looks like in 12 months 

● The knowledge base has enough signal to answer: which part of the product produces the most bugs per sprint, which bug class most often escapes to

production, and whether the front end or back end is the higher source of production risk 

● New features ship with skills pre-written as part of acceptance criteria, not as an afterthought 

● Back-end engineers treat you as a partner in the definition of done, not a gatekeeper at the end of the cycle 

● You have hired at least one QA engineer and defined the roadmap for the rest of the team 

● A measurable reduction in production escape rate compared to the baseline when you joined 

What we are looking for 

Non-negotiable: 

● 3+ years in QA for a fintech or digital lending product — loan origination, payments, or collections 

● Experience testing both front-end and back-end services — API testing, database state validation, and integration testing must be in your toolkit, not stretch goals ● Comfort with failure-path and edge-case thinking — happy-path testers need not apply 

● Proven habit of writing documentation that others actually use — not as a compliance exercise but as a tool 

● Hands-on experience using LLMs (Claude, GPT-4, Gemini) to generate test cases, analyse logs, or review coverage gaps 

● Ability to write basic automation scripts in Python or JavaScript — you do not need to be a developer, but you need to be able to build and maintain simple automated checks 

Strong signal:

● You have built something like a bug knowledge base before — even informally — and can show us what it looks like 

● You have thought about the difference between documentation as a record and documentation as infrastructure 

● You have worked in an environment where a decision made by a system had a direct financial consequence for an end user, and you understood the stakes that came with that 

● You have hired or mentored QA engineers before 

Why this role is different 

Most QA roles are reactive. A bug is found, a ticket is filed, the developer fixes it, QA closes it. The institutional knowledge of why that bug happened lives in someone's head or in a comment nobody will read again. 

We want the opposite: a QA function that compounds. Every bug makes the next release safer. Every production incident makes the test suite smarter. The person who builds that system is not a tester. They are an engineer of quality infrastructure.

Why Join Us? 

● Work directly with Founders: Mikhil Innani, former co-founder of PharmEasy and ex-Product Head at Hotstar, and Diksha Nangia, a former banker and CFA Charterholder 

● Best of both worlds: startup speed + listed company stability 

● High ownership, strong learning curve, and direct business impact ● A fast-paced, collaborative culture that values innovation, ownership, and bold thinking

Learn More About Us 

● Annual Report 2024–25 

● Vision Video 

Location: Bangalore

Experience: 3-5 years

Type: Full-time | On-site

Start: Immediate

Why this role exists

Most companies are using LLMs.

Very few are building an advantage from them.

Right now, LLM cost is our largest margin constraint, and model behavior is still too generic to be defensible.

This role exists to:

• Turn LLM usage into a cost-efficient system
• Build compounding intelligence across accounts
• Create a differentiated analysis layer that competitors can’t replicate

What you’ll do

You will not just build models.

You will own the intelligence and cost structure of the platform.

1. Drive down LLM cost dramatically

• Reduce cost per interaction from ₹40 → ₹2 within 6 months
• Implement:
• Model tiering (right model for the right task)
• Caching strategies (semantic + response caching)
• Batching and async processing
• PTU / reserved capacity optimization
• Ensure performance does not degrade while reducing cost

2. Optimize infrastructure spend

• Reduce cloud spend from ₹20L/month → ₹4L/month
• Work across infrastructure layers (Azure / compute / inference)
• Balance:
• Latency
• Cost
• Throughput
• Treat infra as a first-class optimization problem

3. Build the fine-tuning and learning pipeline

• Design systems where:
• Every interaction improves future performance
• Build pipelines for:
• Fine-tuning
• Feedback loops
• Continuous model improvement
• Ensure the 5th customer deployment is structurally better than the 1st

4. Create a differentiated intelligence layer

• Build analysis systems that:
• Extract signals from interactions
• Improve decision-making
• Drive outcome improvements
• Move beyond responses → insight + action

5. Enable new AI-native product categories

• Identify opportunities where:
• AI enables workflows that were not previously possible
• Build foundational ML capabilities to unlock those categories
• Focus on creation, not just efficiency

6. Commoditize LLM usage internally

• Abstract complexity of LLM usage from product teams
• Build internal systems where:
• Cost is predictable
• Performance is consistent
• Make LLM usage a reliable utility layer

What success looks like

• Cost per interaction drops to ₹2 or lower
• Infrastructure spend reduces 5x without performance loss
• Model performance improves with every deployment
• Platform develops a clear intelligence advantage
• New AI-native capabilities become possible due to your systems

Who you are

• You have 3-5 years of experience in ML / applied AI / systems engineering
• You have worked with:
• LLMs
• Inference optimization
• Production ML systems
• You think in:
• Systems
• Trade-offs (cost vs latency vs quality)
• You care about real-world impact, not just model metrics

What will make you stand out

• Experience with:
• LLM optimization (prompting, fine-tuning, distillation)
• Distributed systems or infra-level optimizations
• High-scale inference systems
• Built systems that:
• Reduced cost significantly
• Improved performance over time
• Strong understanding of:
• Caching strategies
• Model routing
• Evaluation frameworks

Why join

• You will directly impact company margins and scalability
• Your work defines whether we have a defensible ML advantage
• You will build systems that move from:
• Generic AI usage → compounding intelligence

What this role is not

• Not research-only
• Not experimentation without production impact
• Not isolated from product and business outcomes

What this role is

• A builder of ML systems at scale
• A driver of cost and performance optimization
• A creator of long-term competitive advantage

One question to self-evaluate

Can you build ML systems that get cheaper, smarter, and more valuable with every interaction?

Job Description:

You will be working with a team of highly-motivated, young & dynamic teams of engineers & reporting to the Engineering Lead.

• Be honest, reliable & consistent
• Write efficient & clean code
• Have a strong sense of ownership
• Be a part of development & maintenance of Pluang web app, Operations dashboard and other 3rd party products we own
• Contribute to improving the quality of engineering process & engineering culture

• Strong in data structure and algorithms
• Experience in Node.js, Express, API Design & DOM
• Understanding of component based design or other design patterns
• Experience with unit testing, integration testing & continuous integration
• RDBMS and NoSQL databases preferably PostgreSQL, MongoDB
• Good to have passion for investing

• Attractive compensation package - competitive salary, flexible bonus scheme.
• We are always looking for ways to promote and inspire innovation.
• Individual career path - management and technical career growth, enhanced by learning and development program, regular performance assessment, teams of multi-national IT professionals.
• Healthy work environment - company-sponsored medical program, food, and beverage program, open communication.
• Friendly policies to support Work-life balance, team building, and celebrations.

3 - 5 Years of experience, in that min 2 years of experience with PHP MVC frameworks like

Laravel(preferred), CodeIgniter, etc.

Strong Experience in PHP and MySQL and their declarative query languages

Understanding the fully synchronous behaviour of PHP

Strong experience in JavaScript and good to have working knowledge on any JS frameworks like Angular (Preferred) React, Python etc. - Understanding of MVC design patterns

Good understanding of front-end technologies JavaScript, jQuery, Angular, HTML, and CSS3

Knowledge of object-oriented PHP programming

Understanding accessibility and security compliance

Strong knowledge of the common PHP or web server exploits and their solutions

Understanding fundamental design principles behind a scalable application

User authentication and authorization between multiple systems, servers, and environments

Integration of multiple data sources and databases into one system

Familiarity with limitations of PHP as a platform and its workarounds

Creating database schemas that represent and support business processes

Proficient understanding of code versioning tools, such as Git

Basic knowledge of AWS and Shell command

1. Own Architecture and Design for one or more verticals end to end
   Work with stakeholders (Product teams, Partners, UI/UX teams & Vendors) to create right architecture for large scale, large volume consumer facing applications
2. Ability to work in ambiguous environments
3. Be on top of emerging technology and make recommendations to future-proof products and solutions
4. Ensure that systems are architected to be secure and resilient through the effective application of security and Business Continuity principles
5. Lead the definition and validation of architecture principles and standards

Experience : 10+ years

• 5-7+ years of commercial Java development experience
• Experience with well known Open Source frameworks/libraries, like Spring Boot
• Work experience with Docker
• Microservice experience
• Experience with AWS like ECS, Lambda, SQS, RDS, Kinesis streams
• Familiar with iterative development
• Upper-intermediate level of English
• Solid understanding of communication and network protocols (TCP/IP, HTTP).
• At ease with Unix/Linux
• Excellent analytical and debugging skills
• Familiar with both SQL and noSQL databases (MySQL, DynamoDB, Memcached, Redis)
• Practical experience with scaling applications to big user numbers is a plus
• Experience with other programming languages is a plus.

LearnApp's engineers are a small group of people who directly impact the daily lives of thousands of learners across the globe. 
As a software engineer, you are the architect, designer and coder and maintainer of your project. 
In addition, you work closely with the product team to make vision become reality. 
You are dynamic and able to work well both independently and as part of a team.

At LearnApp, we leave all egos at the door and concentrate on the job at hand. 
We value passionate, down to earth, “can do” people who enjoy fine-tuning small details, without losing sight of the big picture. 
We are looking for the type of person who feels uncomfortable when a day goes by without achieving something impactful. 
Someone who is driven to get things done and views obstacles as an exciting challenge that demands a creative solution. 
Above all else, this role requires someone who takes great pride in their work and is inspired and motivated by their role in improving the way thousands of learners receive financial literacy.

As a Backend Software Engineer, you’ll work closely with our engineers to ensure system consistency and improve user experience.

Responsibilities

- Analyze functional requirements and creation of software design
- Design and implement scalable and robust applications
- Design, develop, test, deploy, maintain, and improve software
- Design, shape and implement authentication, authorization, auditing, reporting, and API infrastructure solutions

Qualifications

- Bachelor's degree in Computer Science, a related technical field of study, or equivalent practical experience
- Experience in Object-Oriented Design and programming concepts
- A minimum of 3 years of working experience in a product oriented company
- Programming experience in NodeJS and Typescript or Javascript

Preferred Qualifications

- Experience in building cloud (SaaS) applications, particularly using AWS technologies
- Experience in building serverless applications
- Knowledge of Agile software development methodologies
- Ability to learn other coding languages as needed
- Object-oriented, database design, and SQL skills

Perks

• Good experience and exposure of cloud native architecture, development and deployment on public clouds AWS, Google Cloud etc
• Responsible for Linux server installation, maintain, monitoring, data backup and recovery, securtiy and administration
• Understanding of clusters, distributed architecture, container environment 
• Experience in networking, including linux, software defined networking, network virtualization, open protocols, application acceleration and load balancing, DNS, virtual private networks
• Knowledge of several middleware such as MySQL, Apache etc
• Responsible for managing network storage
• Disaster recovery and incident response planning
• Configuring/monitoring firewalls, routers, switches and other network devices

• Support the globally distributed cloud development and teams by mainitaning the cloud infrastructure labs hosted in a hybrid cloud environment
• Contribute towards optimization of preformance and acost of running the labs