Software Developer

About the Role

We are looking for a strong software engineer who actively uses AI to build better software faster. This is a backend-heavy engineering role where LLMs and AI systems are integrated into real production applications.

You will design, build, deploy, and maintain AI-enabled systems, while maintaining strong engineering discipline and code quality.

Key Responsibilities

• Architect and build scalable backend systems (Python / FastAPI preferred)
• Integrate LLM APIs, RAG pipelines, and AI workflows into production applications
• Deploy and maintain containerized applications on AWS/Azure
• Use AI coding assistants and agents to accelerate development, without compromising code quality
• Convert ambiguous requirements into production-ready systems

Must-Have Skills

• 7+ years of professional software engineering experience
• Strong Python backend experience
• Experience building REST APIs and production systems
• Solid understanding of system design and clean architecture
• Hands-on experience with Docker and Linux
• Experience deploying to AWS or Azure
• Experience integrating LLM APIs into applications
• Experience with embeddings / vector databases / RAG pipelines
• Strong Git and collaborative development workflows
• Ability to operate independently in ambiguous environments

Most importantly:

• Strong engineering fundamentals
• High ownership mindset
• Comfort using AI tools to move fast
• Discipline to maintain structure and quality

Good-to-Have

• Experience with real-time streaming or WebSockets
• Kubernetes deployment experience
• Experience in a fast-paced startup or consulting environment
• Familiarity with agent frameworks or voice/multimodal systems

Screening Requirement

Please include:

• A portfolio of systems you’ve built (especially AI-enabled systems), and
• A short note explaining how you use AI tools in your development workflow.

We are specifically looking for engineers who lean into AI agents and coding assistants, but still understand architecture, performance, and clean code.

Founding Engineer (Bangalore)

The problem:

Business enterprises overpay vendors - on every batch of invoices, on every month because the data that would catch lives in different systems. We are building an AI agent that processes invoices end-to-end, reasons across all the relevant sources, flags genuine discrepancies, and acts - without a human having to investigate each one.

What you will own

Everything engineering. Schema design to deployment to the 2am fix when something breaks in production. There is no tech lead above you. There is no platform team. There is the architecture, you, and the founders. Concretely, this means building:

• A multi-stage agentic pipeline that takes a vendor invoice and produces a structured decision - fully autonomous for clear cases, escalating to human review for genuinely ambiguous ones. We use LangGraph, but if you've built equivalent systems with Temporal, Prefect, or custom state machines with LLM orchestration, that works
• An LLM-powered extraction layer that handles real invoices - scanned PDFs, stamped documents, inconsistent layouts - and returns structured output
• A graph data model that connects invoices to various sources and can traverse those relationships to detect discrepancies
• ERP connectors, GST validation logic, and a write-back layer that closes the loop

What we need

• Strong Python. Async FastAPI, clean service boundaries, tests that actually catch bugs. You have shipped Python backends that handled real production load
• Solid Postgres. Complex queries, schema design, migrations without downtime, row-level security for multi-tenant data. pgvector is a plus - if not, you pick it up fast
• LLM API experience in production. You have called an LLM API for something that real users depended on. You know about structured output, retry logic, cost management, prompt versioning. A side project counts if it was genuinely deployed
• Comfort with graph data models. You understand when a graph is the right structure and when it is not. You do not need deep Neo4j production experience - you need to understand graph relationships conceptually and be willing to learn Cypher. It is a 2-day ramp for the right person
• Working knowledge of deployment. Deployed and operated production workloads on GCP. Cloud Run, Cloud SQL, Cloud Storage, Redis — you're comfortable across the stack. If you've done it on AWS, the translation isn't hard, but GCP is where we are
• You own things. Not "I contributed to" - you designed it, shipped it, and fixed it when it broke. That pattern needs to be visible in your history

Good to have, not mandatory

• Built an agentic pipeline with multiple stages
• Any fintech, P2P domain experience - even tangential
• Worked at a startup with under 20 people
• Has a GitHub, blog, or writeup that shows how you think about a hard technical problem

What you get

• The hardest engineering problem you would have worked on. This is not CRUD with an LLM bolted on
• Real ownership. First engineering hire. Your architectural decisions will be in this product five years from now
• Equity that matters. ESOP - Open to discussion. We are pre-seed - this is a bet, not a guarantee. We will not pretend otherwise
• No meetings tax. You work directly with the founders. The product is specified clearly. You know what you are building and why

Honest about stage: We do not have a production ready infra yet. We have a complete architecture specification and a working prototype. If you need the stability of an established engineering org, this is not the right moment. If you want to build something real from zero and own a meaningful piece of it, it is.

The founders

One of us has spent 20 years building revenue and operational engines at companies where there was no playbook - part of the pilot team that established the world's largest search company's direct sales operations in India, managed global operations for a global mobile advertising platform, scaled a B2C platform to become one of India’s leading edtech platforms and most recently worked on building an enterprise Agentic Voice AI platform. The other has spent 15 years taking AI from demo to production in domains where failure is expensive - voice, lending, and conversational systems across a Series D conversational AI company, a major telco, a Big 4, and a leading NBFC.

Two IIT/IIM alumni who have both watched AI work in enterprise, and know exactly what it takes to get it there. We are not building this product because it sounds interesting. We are building it because we have both sat across the table from CFOs who know they are losing margin and have no tool capable of doing anything about it.

Core AI Backend Engineer – LLM Fine-Tuning

You know that moment when you don’t just debug code — you train a model, fine-tune it, and suddenly it understands your domain better than you expected? That’s the kind of magic we’re looking for.

We’re building something that turns chaotic social video data into crystal-clear business intelligence. Not just another API — but AI-backed architecture fine-tuned to our world. Systems that marketing teams thank you for, because they feel the intelligence, not just the infrastructure.

Either you feel the craft when you read this, or you don’t. This isn’t just another backend role. This is where you bring together scalable systems and cutting-edge LLMs to build something the world hasn’t seen before.

Who We Are

We’re a small, global team that ships fast. Every line of code and every model choice affects millions of video analysis requests.

Our engineers don’t just build APIs — they architect solutions, they optimize at scale, and now, they fine-tune models to make AI work in the real world. Our CPTO still codes. Our senior engineers make complexity look effortless. Our backend team sets a standard that others ask how we move so fast.

What We Need

We need someone who’s lived both sides of this life:

• Backend excellence: building high-scale, high-performance systems.
• LLM fine-tuning: hands-on with open-source models, not just calling APIs.

Someone who can sit with a requirement at 2pm and by 6pm not only has endpoints working, but also has a fine-tuned model running behind them — customized to our use case.

Your Craft

• JavaScript/TypeScript & NodeJS as core backend tools.
• Next.js for full-stack where needed.
• Rust when performance is non-negotiable.
• Golang/Python as comfortable tools of choice.
• MySQL/Postgres/Redis — wielded with intention.
• AWS ecosystem — your playground, not your puzzle.
• LLM/AI integration you’ve actually shipped.
• Open-source LLM fine-tuning experience:
• Bringing in open-source models (LLaMA, Mistral, Falcon, etc.).
• Fine-tuning/adapting them for specific domains.
• Optimizing for inference cost, latency, and accuracy.

The Reality

The work is beautifully complex. The scale is real and growing. The problems are the kind that wake you up at 3am with solutions.

If you get your energy from building backend systems and adapting LLMs to make them smarter for real-world use, you’ll probably fall in love with what we do. If you’re only interested in APIs without touching models, this won’t be your thing — and that’s completely okay.

How to Apply

If you’re reading this thinking “finally, a team that actually cares about real AI engineering” — we’d love to see something you’ve built.

Not just a resume. Show us your craft:

• An LLM fine-tuning repo.
• A domain-adapted model you worked on.
• A system design where you combined backend and AI.
• Or even a short write-up or voice note explaining what you’ve fine-tuned.

We’re genuinely excited to see what you’ve done and have a meaningful conversation about whether this could be magic for both of us.

Job Description - 

Role - Sr. Python Developer

Location -- Manyata Tech Park, Bangalore 

Mode - Hybrid

Required Tech Skills:

• Experience in Python
• Experience in any Framework like Django, and Flask.
• Primary and Secondary skills - Python, OOPs and Data Structure
• Good understanding of Rest Api 
• Familiarity with event-driven programming in Python 
• Good analytical and troubleshooting skills

Job Summary:

As a Shopify App Developer at [Your Company Name], you will be responsible for designing, developing, and maintaining custom applications for the Shopify platform. You will collaborate with cross-functional teams to create solutions that meet our clients' needs and improve their eCommerce operations. The ideal candidate will have a strong background in Shopify app development, excellent problem-solving skills, and a passion for delivering exceptional user experiences.

Key Responsibilities:

• App Development: Design, develop, and deploy custom Shopify apps using Shopify’s API, Polaris, and other relevant technologies.
• Customization: Customize and extend Shopify’s existing functionalities to meet specific client requirements.
• Integration: Integrate Shopify apps with third-party services, APIs, and data sources as needed.
• Maintenance & Support: Troubleshoot and resolve issues related to Shopify apps and provide ongoing support and maintenance.
• Collaboration: Work closely with project managers, designers, and other developers to ensure that app solutions align with project goals and client expectations.
• Testing & Quality Assurance: Conduct thorough testing of applications to ensure reliability, performance, and adherence to Shopify’s standards.
• Documentation: Create and maintain clear documentation for code, processes, and app functionality.
• Innovation: Stay updated with the latest Shopify developments, industry trends, and best practices to continuously improve app functionality and user experience.

Qualifications:

• Experience: Proven experience in developing Shopify apps, including a portfolio of past projects or apps.
• Technical Skills: Proficiency in Shopify’s APIs, Liquid templating language, JavaScript, HTML, CSS, and familiarity with Shopify Polaris design system.
• Programming Languages: Strong knowledge of backend programming languages such as Ruby, PHP, or Node.js.
• Database Management: Experience with database technologies such as MySQL, MongoDB, or PostgreSQL.
• Problem-Solving: Excellent problem-solving skills with the ability to troubleshoot and resolve complex technical issues.
• Communication: Strong verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Team Player: Ability to work effectively both independently and as part of a team in a fast-paced environment.

• Two years' experience as a Node.js developer.
• Extensive knowledge of JavaScript, web stacks, libraries, and frameworks.
• Knowledge of front-end technologies such as HTML5 and CSS3.
• Superb interpersonal, communication, and collaboration skills.
• Exceptional analytical and problem-solving aptitude.
• Great organizational and time management skills.

Responsibilities:

• Supporting system design, development, and maintenance
• Taking responsibility for personal technical quality standards within the team
• Assisting in defining structured practices, especially in source code management, building, and deployment
• Optimizing applications for maximum speed and scalability
• Taking initiatives to build better and faster solutions to the problems of scale

Requirements:

• Experience with NodeJS for at least 3-5 years
• Experience with technologies such as Docker, Kubernetes, and AWS
• Experience with other programming languages such as Go, Python, and Java
• Experience being in a leadership/ mentorship position for 2-3 years
• Should have built systems that have scaled to at least ten thousand users
• Should have an open mind to learn and experiment with new technologies as our needs change