Cutshort Lightning

Must-Have Skills

• Minimum 3 years of experience in Data Engineering / Analytics Engineering / Fintech Data roles
• Must have worked on SMS Parsing, intelligent platform, converting RAW customer SMS data into structured actionable financial signals and enabling downstream usage of SMS derived variables
• Must have established a continuous learning cycle to expand parser coverage
• Experience in Lending / NBFC / Fintech domain
• Experience working with Bureau, SMS, Device, or Banking data
• Strong Python and SQL (production level)
• Experience handling unstructured data (SMS, logs, JSON, APIs)
• Experience building data pipelines, schedulers, and cron jobs
• Strong database design and data modelling skills
• Ability to work in a startup environment with high ownership
• Familiarity with modern platforms like AWS, Snowflake, Google BigQuery, Redshift

Good to Have

• Experience in STPL, especially less than 25K ticket size
• Experience with streaming (Kafka/Kinesis) and orchestration (Airflow or Step Functions)
• Experience with feature stores and risk analytics datasets
• Knowledge of regex, NLP basics for SMS parsing
• Experience supporting real-time decision engines/underwriting systems

Role Summary

This role will be responsible for owning the end-to-end data-structuring layer across the organisation. The individual will transform large volumes of raw, unstructured, and semi-structured data (such as SMS, device, bureau, and app data) into clean, standardised, and analysis-ready datasets. These structured datasets will directly power risk analytics, fraud detection, marketing insights, collections strategy, and policy decisioning.

Key Objective of the Role

Ensure all raw lending data (SMS, Bureau, Device, AA, App logs) is captured, parsed, structured, and stored in a clean analytics-ready format inside databases (PostgreSQL, DynamoDB, AWS stack) so that the Risk and Data Science team can directly use it for feature creation, policy building, and portfolio monitoring.

Core Responsibilities

1. End-to-End Data Ownership

• Design, build, and maintain end-to-end data pipelines (batch + streaming) using AWS native services (Glue, Lambda, Step Functions, Kinesis, S3, Athena, Redshift, EMR/Spark, etc.): ingestion

→ parsing → structuring → storage

• Work closely with Tech, Product, and Data Science to define what data should be captured
• Maintain data documentation, data dictionaries, and schema governance
• Ensure data quality, consistency, and version control

1. Unstructured Data Processing (Highest Priority)

• Parse raw SMS dumps and categorise into salary, EMI, loan apps, collections, credits, debits, OTP, etc.
• Process device fingerprint, behavioural logs, and vendor data (FinBox, AA, Bureau APIs)
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• Convert JSON, logs, and raw API responses into structured feature tables
• Build regex/keyword-based parsers for financial SMS classification

1. Feature Implementation (From Risk & Data Science Team)

• Implement feature creation logic provided by Risk/Data Science team
• Translate business and policy logic into SQL/Python pipelines
• Create reusable feature layers for underwriting, fraud, collections, and monitoring
• Maintain a feature store for consistent model and policy usage

1. Lending Data Understanding (Domain-Specific Requirement)

• Work with Bureau data
• Structure SMS-derived financial variables (income, stress, EMI signals)
• Work with Account Aggregator and bank transaction datasets
• Understand fintech alternate data used in underwriting and fraud detection

1. Data Pipelines & Automation

• Build and maintain ETL/ELT pipelines using Python & SQL
• Create cron jobs for automated data ingestion and feature refresh
• Automate vendor data pulls (Bureau, SMS SDK, AA, device data)
• Ensure low-latency pipelines for real-time underwriting use cases

1. Database Structuring & Storage Architecture

• Structure clean datasets in PostgreSQL (analytics layer)
• Manage raw data storage in DynamoDB / S3 data lake
• Design normalized and denormalised tables for risk analytics
• Optimise database performance for large-scale query workloads

1. Dashboards & Readable Data Layer

• Create analytics-ready datasets, implement & write Metabase queries and convert into dashboards (Metabase / Power BI)
• Enable self-serve data access for Risk, Business, and Founders
• Support ad-hoc analysis requirements from leadership

1. Cross-Functional Collaboration (Very Important)

• The role requires close collaboration with data science, tech, product, and business teams to ensure reliable data pipelines, well-defined schemas, API integrations, logging architecture and high data quality, enabling faster and more accurate decision-making across lending workflows.

Tech Stack (Current Environment)

• AWS Services
• PostgreSQL (Primary analytics DB)
• DynamoDB (Raw/NoSQL storage)
• Python (Pandas, NumPy, ETL frameworks)
• Advanced SQL
• APIs, JSON, and Log Data Handling

About the company

The client is a US-based cybersecurity startup prevents, detects, and responds to software supply chain attacks by analyzing behavior across the full software development lifecycle for both developers and AI coding agents. They are building a vertical AI agent for supply chain security across three pillars: securing AI agents on developer machines, OSS package security, and CI/CD security, covering the entire agentic pipeline from dev environment to cloud.

About the Job

We are seeking backend engineers to build and maintain the CI/CD security platform's backend systems and components (GitHub Actions). This high-impact role involves setting best practices and owning engineering processes, with contributions used by thousands of developers globally. Our primary languages are Golang and Node.js.

Requirements

• 2–5 years of experience, strong engineering fundamentals (cyber security background not mandatory), AI-native mindset, comfortable with a hands-on zero-to-one environment. We use Golang as our primary language.
• Must-haves: Golang backend programming; AWS/Azure/GCP background; scalable/fault-tolerant system design.
• For all engineering positions, prior early-stage startup experience is a must-have requirement.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Solid understanding of software development principles, design patterns, and best practices.Expertise in building scalable and fault-tolerant systems.
• Strong collaborative and problem-solving skills.
• Self-motivated, creative thinker with a drive for continuous improvement.
• Experience in a startup or high-impact, outcome-driven environment.

Location

India remote. Candidates should be able to overlap a few hours with Pacific Time (PT) when working on urgent customer issues as required.

Responsibilities

• Design, develop, and maintain robust, scalable software solutions.
• Architect and implement CI/CD components (GitHub Actions).
• Deliver features incrementally in quick iterations.
• Write clean, efficient, and maintainable code following industry best practices.
• Conduct code reviews and provide constructive feedback.
• Troubleshoot and debug complex software issues promptly.

Why Join Us

• The company is at the forefront of supply chain security research and product development. They were the first to detect several major supply chain attacks in 2025 and 2026 such as the axios npm compromise, tj-actions, etc
• Their research and findings are regularly cited by major publications such as Bloomberg, TechCrunch, Hacker News, and Dark Reading. The Cybersecurity and Infrastructure Security Agency (CISA), the primary cybersecurity agency for the US federal government, has published several cybersecurity advisories citing our work
• In addition to having several enterprise customers, we have been adopted by more than 15,000 open-source projects, including projects from Microsoft, Google, Amazon, Datadog, and others.
• Engineers joining now get to work on hard, high-impact problems at the intersection of security, AI, and open source, with meaningful equity upside at an early stage.

Location: Bengaluru (Work from Office – 6 Days a Week)

About the Role

We're looking for a Software Development Engineer III (SDE-3) to join our growing engineering team. We're seeking engineers who have previously built, scaled, or significantly contributed to applications serving 100K+ users. You'll be joining a small, high-impact team, so we're looking for engineers who thrive on ownership, move quickly, and enjoy solving challenging technical problems.

We are technology agnostic and value strong engineering fundamentals over expertise in any particular language or framework. Whether your background is Backend, Frontend, or Full Stack, we'd love to hear from you.

What You'll Do

• Design, develop, and maintain scalable, reliable, and high-performance applications.
• Build robust, production-ready software that delivers exceptional user experiences.
• Take end-to-end ownership—from design and development to deployment and production support.
• Work closely with Product, Design, and Engineering to deliver impactful features.
• Write clean, maintainable, and well-tested code following engineering best practices.
• Leverage AI-assisted development tools (such as GitHub Copilot, Cursor, Claude Code, ChatGPT, or similar) to improve development speed, code quality, debugging, testing, and overall engineering productivity.
• Participate in architecture and design discussions, balancing scalability with simplicity.
• Troubleshoot production issues and continuously improve system performance and reliability.
• Contribute to a collaborative engineering culture through code reviews and knowledge sharing.

Must-Have Qualifications

• 4–6 years of professional software development experience.
• Strong proficiency in at least one high-level programming language, such as Python, Go (Golang), C#, JavaScript/TypeScript, Kotlin, Scala, or Ruby.
• Strong understanding of Data Structures, Algorithms, Object-Oriented Programming, and System Design.
• Hands-on experience building, scaling, or maintaining production applications with a user base of 100K+ users.
• Proven experience working on high-traffic, large-scale consumer or B2B products where performance, reliability, and scalability were critical.
• Experience developing modern Backend, Frontend, or Full Stack applications.
• Strong understanding of APIs, databases, and scalable application architecture.
• Demonstrated ability to effectively use AI coding assistants to accelerate software development while maintaining high standards of code quality and engineering best practices.
• Excellent problem-solving skills and a strong sense of ownership.

Preferred Qualifications

• Experience working on platform or infrastructure products is highly preferred.
• Experience with cloud platforms (AWS, GCP, or Azure).
• Familiarity with microservices, distributed systems, CI/CD, and containerization.
• Experience working in product companies or fast-paced startup environments.

Who You Are

• You enjoy working in small, fast-moving teams where every engineer has significant ownership.
• You're comfortable wearing multiple hats and contributing across different parts of the stack when needed.
• You've previously worked on products operating at scale and understand the engineering challenges of supporting 100K+ active users, including performance optimization, reliability, and scalability.
• You have a product mindset and care deeply about performance, scalability, and user experience.
• You're a proactive problem solver who enjoys taking initiative and driving projects independently.
• You embrace modern engineering practices, including the effective use of AI tools to enhance productivity without compromising software quality.
• You value collaboration, continuous learning, and building high-quality software.

Why Join Us?

• Join a high-impact engineering team with significant ownership and autonomy.
• Solve challenging engineering problems with a focus on performance, scalability, and reliability.
• Collaborate with talented engineers in a fast-paced, product-driven environment.
• Build software that directly impacts thousands of users while accelerating your technical growth.

About the Company:

A fast-growing, seed-funded AI startup is building the next-generation AI Operating Layer for enterprise IT operations. The platform leverages Agentic AI and enterprise automation to transform how IT services are delivered. As the engineering team rapidly scales, they are looking for an experienced QA Automation Engineer to build a robust automation-first testing practice.

Role Overview

We are looking for a hands-on QA Automation Engineer who can own the test automation strategy for a modern AI-powered platform. This is an automation-first role with minimal manual testing, requiring close collaboration with engineering and product teams to ensure fast, reliable, and high-quality releases.

Key Responsibilities:



• Design, build, and maintain scalable automation test frameworks.
• Automate UI, API, regression, and end-to-end test scenarios.
• Work closely with developers to ensure high product quality.
• Integrate automated tests into CI/CD pipelines.
• Perform API, functional, regression, and integration testing.
• Improve release quality through automation and continuous testing.
• Support performance, security, and reliability testing initiatives.
• Own automation from design through production validation.

Required Skills

• 5–8 years of experience in QA Automation.
• Strong hands-on experience with automation frameworks such as Selenium, Playwright, Cypress, or similar.
• Experience with API Testing and automation.
• Knowledge of REST APIs and backend testing.
• Experience with CI/CD tools (Jenkins, GitHub Actions, Azure DevOps, etc.).
• Strong debugging and analytical skills.
• Good understanding of SDLC, STLC, and Agile methodologies.
• Excellent communication and collaboration skills.

Good to Have

• Performance or Load Testing.
• Security Testing.
• Experience testing AI/ML or GenAI applications.
• Cloud platforms (AWS/Azure/GCP).
• Docker or Kubernetes exposure.
• Scripting using Java, Python, or JavaScript.

Why Join?

• Be part of the founding engineering team of a well-funded AI startup.
• Build an automation-first quality engineering practice from the ground up.
• Work directly with experienced founders and senior engineers.
• Solve challenging engineering problems in AI, enterprise automation, and distributed systems.
• High ownership, fast-paced environment, and significant growth opportunities.

About the Company:

A well-funded AI startup is building enterprise-grade Agentic AI infrastructure that enables autonomous systems to safely execute complex workflows across enterprise environments.

The company is building its founding engineering team and offers the opportunity to work directly with experienced founders on cutting-edge AI products.

Role Overview:

We're looking for an experienced engineer who has built production-grade AI Agents or Agentic AI systems.

You'll design and build the core infrastructure that powers autonomous AI agents, including reasoning, planning, tool execution, memory, orchestration, evaluation, and reliability.

Key Responsibilities:

• Design and build production-ready AI agent infrastructure.
• Develop agent orchestration, planning, routing, and memory systems.
• Build guardrails, validation, retries, rollback, and failure recovery mechanisms.
• Develop evaluation, tracing, and observability frameworks for AI agents.
• Integrate AI agents with enterprise platforms and APIs.
• Own AI platform architecture from design through production deployment.

Required Skills:

• 6–10 years of software engineering experience.
• Hands-on experience building production AI Agents.
• Strong understanding of LLMs, Agentic AI, and AI orchestration.
• Experience with LangGraph, Semantic Kernel, or similar agent frameworks.
• Strong backend engineering and distributed systems experience.
• Experience with Python, Node.js, or TypeScript.
• Knowledge of RAG, multi-agent systems, planning agents, and tool calling.
• Experience with PostgreSQL, Redis, AWS, and Docker.
• Strong engineering ownership and problem-solving ability.

Good to Have:

• LLM evaluation frameworks.
• AI observability and tracing.
• Workflow engines and state machines.
• Terraform.
• Microsoft Graph / Microsoft 365 integrations. 

About the Role

You'll be at the forefront of designing and implementing robust data platform solutions that power advanced analytics, AI, and machine learning. Working with modern cloud technologies, you'll build scalable data foundations that enable clients to make smarter, data-driven decisions.

Key Responsibilities

• Build scalable data pipelines using Snowflake, AWS, GCP, and Databricks.
• Design and optimize data models for AI and machine learning workloads.
• Develop reliable data foundations for MLOps, governance, and data lineage.
• Integrate data from multiple sources into modern data platforms.
• Leverage Snowpark ML and Snowflake's native AI capabilities.
• Ensure data platforms are secure, scalable, and high-performing.

What We're Looking For

• 5+ years of hands-on experience with Snowflake.
• Strong proficiency in SQL and Python.
• Experience with AWS, Azure, or GCP.
• Knowledge of cloud storage services such as S3, ADLS, or GCS.
• Strong understanding of Dimensional Modeling and Data Vault.
• Experience with Scala or Java is a plus.

Tech Stack

• Data Warehouse: Snowflake
• Programming: SQL, Python, Scala (Good to Have), Java (Good to Have)
• Cloud: AWS, Azure, GCP
• Storage: S3, ADLS, GCS
• AI/ML: Snowpark ML, MLOps

Perks & Benefits

• Public Speaking & Communication Program
• Mentoring Program with Senior Support Leads
• 360° Progress Reviews
• Weekly Learning Sessions & Guilds
• Paid Certifications
• Hackathons & Innovation Days
• Recognition & Rewards Programs
• Team Socials & Annual Offsites
• Employee Assistance Program (24/7 Wellbeing Support)

The Data People Shaping Tomorrow

Our client helps organizations unlock the power of data through modern cloud, analytics, and AI solutions. We believe in creating an environment where talented technologists can learn, innovate, and make a real impact while building cutting-edge data platforms for global clients. If you're passionate about data engineering and want to work with the latest technologies in AI, cloud, and analytics, we'd love to hear from you.

Key Responsibilities:

Backend Ownership

• Own the design, evolution, and reliability of mission-critical backend systems.
• Ensure scalability, performance, maintainability, and overall system health.
• Lead technical initiatives to address scaling challenges, technical debt, and architectural improvements.

System Design & Architecture

• Drive both High-Level Design (HLD) and Low-Level Design (LLD).
• Design scalable APIs, data models, service boundaries, and asynchronous workflows.
• Make sound engineering trade-offs balancing delivery speed with long-term system health.

Code Quality & Engineering Excellence

• Improve backend code quality through architecture reviews, code reviews, and refactoring.
• Simplify complex codebases and establish maintainable engineering patterns.
• Introduce best practices and guardrails to improve long-term maintainability.

Database & Performance Optimization

• Optimize PostgreSQL performance through schema design, indexing, query optimization, and tuning.
• Improve application performance using caching strategies and asynchronous processing.
• Design and operate analytics pipelines using ClickHouse or similar large-scale data systems.
• Work with messaging systems such as RabbitMQ or equivalent.

Technical Leadership

• Mentor backend engineers on architecture, debugging, and engineering best practices.
• Influence technical direction through thoughtful design discussions and strong technical reasoning.
• Raise overall engineering standards across teams.

Production Ownership

• Own production stability, incident management, and root cause analysis.
• Improve observability, monitoring, debugging, and operational excellence.
• Drive long-term reduction in production incidents and operational overhead.

Required Skills & Experience

Must Have

• 7+ years of backend engineering experience.
• Strong expertise in Node.js.
• Deep experience with PostgreSQL, including performance tuning and optimization.
• Experience designing and operating distributed backend systems.
• Strong understanding of system design, scalability, and microservices architecture.
• Experience owning backend services end-to-end—from architecture to production support.
• Strong debugging and problem-solving skills.
• Experience improving code quality, maintainability, and engineering standards.

Good to Have

• Experience with RabbitMQ or similar messaging systems.
• Experience with ClickHouse or large-scale analytics platforms.
• Experience deploying and managing applications on AWS.
• Strong knowledge of observability, monitoring, and production reliability.

What We're Looking For

Engineering Mindset

• Passion for improving existing systems rather than simply building new ones.
• Ability to simplify complex architectures and create maintainable solutions.
• Strong focus on writing clean, readable, and scalable code.
• Testing mindset with emphasis on reliability and long-term quality.
• Ability to evaluate technical trade-offs and design for future scalability.

Leadership Without Authority

• Influence technical decisions through expertise and clear reasoning.
• Challenge scope or timelines when necessary to protect system health.
• Mentor engineers and elevate overall engineering standards.
• Lead by example through hands-on technical excellence.

Why Join Vahan?

• Unlimited Paid Time Off (PTO)
• Comprehensive Medical Insurance
• Monthly Wellness Leaves
• Competitive Compensation
• Opportunity to solve large-scale engineering challenges impacting millions of users
• Ownership-driven engineering culture with significant technical autonomy
• Work alongside exceptional engineers building products that create meaningful social impact

Role: Backend Developer (Node.js)

Key Responsibilities

Backend Development

• Build scalable, high-performance backend services and REST APIs using Node.js.
• Develop robust, maintainable, and production-ready applications.

Database Optimization

• Design efficient database schemas.
• Optimize queries, indexing, and overall database performance.
• Work extensively with PostgreSQL or MySQL.

Frontend Collaboration

• Collaborate closely with frontend engineers to integrate APIs.
• Basic understanding of React or Angular is a plus.

System Design

• Participate in both Low-Level Design (LLD) and High-Level Design (HLD) discussions.
• Design systems with scalability, security, and reliability in mind.

Cloud & Infrastructure

• Deploy and manage applications on AWS.
• Utilize Redis for caching and performance optimization.

Code Quality

• Write clean, maintainable, and well-documented code.
• Participate in code reviews and follow engineering best practices.

Testing & Debugging

• Write comprehensive test cases.
• Ensure backward compatibility.
• Debug and resolve issues related to functionality, performance, and scalability.

Required Skills & Experience

Must Have

• 2+ years of backend development experience.
• Strong proficiency in Node.js.
• Experience with PostgreSQL or MySQL.
• Good understanding of REST APIs.
• Experience with AWS cloud services.
• Knowledge of distributed systems and microservices architecture.
• Experience with Redis or similar caching technologies.
• Strong understanding of system design concepts.
• Excellent debugging and problem-solving skills.
• Focus on writing scalable, reliable, and testable code.

Good to Have

• Basic knowledge of React or Angular.
• Experience working in fast-paced startup environments.

Why Join Vahan?

• Unlimited Paid Time Off (PTO)
• Comprehensive Medical Insurance
• Monthly Wellness Leaves
• Competitive Compensation
• Opportunity to work on products impacting millions of users
• Fast-paced, high-growth startup backed by leading investors
• Ownership-driven engineering culture with meaningful technical challenges

We’re looking for a hands-on builder who can thrive in a fast-paced startup environment. You’ll own features end-to-end, from designing architecture to writing clean, reusable code, testing, deploying, and iterating fast.

What you’ll do

• Build and scale web + mobile applications using Python (Django) and React Native/React.
• Design, develop, and deploy cloud-native solutions using AWS services.
• Work with both SQL and NoSQL databases (PostgreSQL, DynamoDB).
• Ensure applications are secure, scalable, and performance-optimized.
• Collaborate closely with product, design, and business teams to ship features at lightning speed.
• Take ownership of problems - from brainstorming and architecture to debugging in production.
• Bring startup energy: move fast, learn fast, and don’t be afraid to get your hands dirty.

What we’re looking for

• 1-3 years of experience in full-stack development.
• Strong experience in Python (Django).
• Proficiency in React Native/React, with solid knowledge of JavaScript.
• Experience with AWS services (serverless, EC2, S3, etc.).
• Experience with docker or kubernetes.
• Hands-on with databases: PostgreSQL, DynamoDB.
• Strong understanding of data structures, design patterns, and microservices architecture.
• Proficiency with Git and version control workflows.
• A product-first mindset, balancing code quality with speed of execution.
• Great communication skills, detail-oriented, and a true team player.
• Bonus - If you are an AI native developer and try to solve problems using AI

We are looking for an Engineering Lead to own the entire technology stack — from onboarding and underwriting to disbursals, repayments, and collections — and to build the engineering function into something genuinely AI-native. 

What You'll Own 

● Full tech stack: backend, frontend, infrastructure, integrations, and data pipelines 

● Real-time underwriting and decisioning systems 

● LOS/LMS architecture — onboarding, disbursals, repayments, and collections

● Integrations with bureaus, KYC providers, account aggregators, and payment gateways 

● Reconciliation systems — disbursement, repayment, and NACH reconciliation end-to-end 

● AWS infrastructure: scaling, reliability, uptime, and cloud cost ownership ● Data infrastructure for the credit and risk team — feature pipelines, model serving, experiment infrastructure 

● Engineering leadership: hiring, sprint planning, code reviews, and execution standards 

● Compliance systems: RBI guidelines, DPDP, KYC/AML, e-NACH, e-sign 

AI-Native Engineering 

This is a core part of the role, not a bonus. You will build a machine-readable knowledge base of the entire codebase — architecture, data models, service contracts, coding standards, decision history — so that AI agents working on code have the context to produce accurate, consistent output. You will build skills for code review, developer onboarding, and recurring engineering workflows. You will build a code review pipeline where agents do the first pass on every pull request. The knowledge base and the skills improve over time as the team grows and the product evolves. 

What We're Looking For 

● 7+ years in software engineering, with at least 2 years leading teams or architecture

● Strong hands-on experience with Python, Django, and React Native

● Deep expertise in AWS and cloud-native architecture 

● Experience with both SQL and NoSQL databases 

● Strong understanding of distributed systems, microservices, and API design

● Experience owning reconciliation or payment flow infrastructure in a lending or payments context

● Prior experience in fintech / NBFC / digital lending — mandatory

● Strong understanding of the full loan lifecycle — mandatory 

● You have used LLMs seriously as engineering tools and have strong opinions about what makes AI-assisted development produce good output versus mediocre output 

Bonus: Kubernetes / Kafka, AI/ML-driven underwriting, Account Aggregator framework, e-NACH / e-Sign / Video KYC integrations 

What Success Looks Like 

● scales with strong uptime, performance, and reliability

● Reconciliation runs cleanly — no financial discrepancies surface late ● A new engineer joins and is writing standard, correct code within their first week

● The credit team is never blocked on an engineering dependency 

● Engineering health metrics are tracked and visibly improving 

● AI agents are doing the structured first pass on code reviews, and the system gets smarter over time