Software Developer - 1

Enterprise AI is moving fast, and most businesses are still running on manual workflows, human-routed tickets, and reactive support operations. Singularium exists because intelligence is now abundant and cheap, and the businesses that rewire their operations around it will outrun those that do not.

The company builds agentic AI solutions across interaction management and enterprise workflows: intelligent ticket routing, ticket automation, quality assurance, audit automation, and conversational AI products. Its proprietary platform, StepZero, orchestrates these workflows across multiple customers.

Singularium is pre-seed, twenty people, and already working with paying clients. The founders and leadership are intellectually curious, professionally rigorous, and building from scratch with no hierarchy in between.

As a Software Developer at Singularium Technologies, you will own the full development cycle for agentic AI solutions built on the StepZero platform.

You will scope customer problems, design and build pipelines for document intelligence, RPA, and interaction management, and deploy solutions directly with clients. The role asks for strong Python fundamentals, comfort with AI in production, and first-principles problem-solving.

You will work closely with the Associate Director and engage with customers from early in the process.

You own the full software development lifecycle on customer-facing agentic AI solutions.

• Document intelligence pipelines. Build and maintain pipelines that extract, process, and act on information from client systems.
• RPA-based automation. Develop Playwright-driven workflows that log into portals, scrape data, and simulate actions to resolve or dispose tickets automatically.
• Agentic interaction management. Build LLM-powered solutions that access customer support portals and automate ticket resolution end to end.
• StepZero workflow solutions. Create and deploy customer-specific workflow orchestrations on Singularium's proprietary platform.
• Customer scoping and deployment. Translate client problem statements into technical designs and own the solution through to live deployment.
• Infrastructure fundamentals. Containerize and manage solutions using Docker and Kubernetes across pilot and production environments.

• Built and shipped Python projects independently. You have written production-grade Python, not just coursework, and can show what you built.
• Worked with AI or LLMs in a real environment. You have integrated an LLM or ML model into a running system and dealt with what breaks in production.
• Figured out architecture from first principles. When there was no playbook, you reasoned through the design yourself and made it work.
• Comfortable with Docker and Kubernetes basics. You have containerized an application and understand how deployments are managed.
• Built things on your own time. Weekend projects, personal tools, or open-source contributions show you build because you want to, not because you were asked.
• Operated in a fast, ambiguous environment. You have worked somewhere with thin process and high stakes, and you moved without waiting for direction.

• Own the problem, not just the ticket. Pick up a customer requirement and carry it from scoping to deployed solution yourself.
• Work directly with customers. Client conversations, escalations, and solution reviews are part of the job from week one.
• Decide from first principles. When there is no precedent, reason through the architecture and make the call.
• Move fast on pilots. Scope quickly, build a working version, and iterate with the client in real time.
• Keep the feedback loop short. Debug in production, talk to the client, and ship the fix; the cycle is tight here.
• Build in the open. No hierarchy, no bureaucracy; your work is visible to founders and customers from day one.
• Bring curiosity to new tools. The stack evolves with the problems; pick up what the solution needs and run with it.

Cash compensation of ₹9L to ₹12L a year, with no equity component at this stage. You report to the Associate Director and own the full development lifecycle on live customer deployments. The role gives you direct exposure to real enterprise AI problems and the chance to grow with a company being built from scratch.