Full Stack Developer

Location: New Delhi

About VisibilityStack.ai

VisibilityStack was founded by the Founders of FirstPrinciples ($8m+ ARR) and Listnr.ai (3.5mn+ users across 200 countries) to solve for one of the most painful problems to exist in this decade - AI search visibility.

VisibilityStack.ai helps brands win visibility in the new search layer - across AI search, generative engines, and modern discovery surfaces.

We are building an AI-native SEO/GEO platform that helps companies understand, improve, and scale how they appear across traditional search, LLM-powered search, answer engines, and agent-driven discovery workflows.

Our product sits at the intersection of:

AI search and generative engine optimization

agentic workflows and automation

large-scale data collection and analysis

modern SaaS product engineering

applied AI infrastructure

We care deeply about shipping fast without compromising quality or security, building useful product experiences, and turning cutting-edge AI capabilities into reliable software that customers use every day.

The Role

We’re looking for a Full Stack AI Engineer who is highly product-minded and excited about building AI-native software from end to end.

This is not a narrow frontend or backend role. You’ll work across the stack - from APIs, workflow engines, and data systems to polished product surfaces - while helping design and ship the core intelligence layer behind VisibilityStack.ai.

You should be comfortable building with modern AI tooling, orchestrating workflows, integrating LLMs and external tools, and turning messy real-world requirements into clean product experiences. The ideal candidate has strong software engineering fundamentals, a bias for shipping, and hands-on experience with AWS-based systems.

What You’ll Work On

1) Build AI-native product workflows

Design and ship product features powered by LLMs, retrieval systems, and agentic workflows

Build systems that automate SEO/GEO research, content intelligence, brand monitoring, query expansion, and recommendation generation

Create workflow-driven features that connect models, tools, APIs, and data pipelines into production-ready user experiences

Develop internal AI tooling for experimentation, prompt iteration, evaluation, and rapid feature development

2) Develop full stack product systems

Build scalable backend services and APIs for core product workflows

Develop fast, intuitive frontend experiences using React or similar modern frameworks

Create internal dashboards, operator tools, and customer-facing interfaces for monitoring, debugging, and workflow control

Write clean, maintainable, well-tested code across the application stack

3) Build agentic software and orchestration layers

Design and manage multi-step AI workflows with tool use, state management, retries, fallbacks, and validation

Build integrations that allow AI systems to interact with internal services, external APIs, databases, and data sources

Implement session handling, persistence, memory, and context management for agent-driven applications

Design knowledge and retrieval layers using vector databases, embeddings, and document pipelines

Build systems for evaluating agent outputs, monitoring behavior, debugging execution failures, and improving reliability over time

4) Build data and intelligence infrastructure

Develop ingestion pipelines for structured and unstructured data across search, content, and web intelligence sources

Build backend systems for crawling, processing, scoring, and serving product insights

Work with ranking, classification, extraction, and summarization workflows in production

Collaborate on systems that turn raw data into actionable product recommendations

5) Own cloud infrastructure and deployment on AWS

Build and manage services deployed on AWS

Work with cloud-native architectures for compute, storage, queues, and observability

Improve performance, scalability, and cost efficiency across product and AI workloads

Support containerized services and production deployment pipelines

Help define best practices around reliability, monitoring, and infrastructure hygiene

6) Drive engineering quality and product velocity

Collaborate closely with product and leadership on feature design and prioritization

Participate in technical design, architecture reviews, and code reviews

Bring strong engineering judgment around tradeoffs, speed, and maintainability

Contribute to a culture of ownership, experimentation, and high standards

What We’re Looking For:

Core Requirements

1-4 years of experience in software engineering, full stack development, or backend-heavy product engineering

Strong fundamentals in computer science, data structures, algorithms, and systems design

Strong proficiency in Python

Experience building backend services using FastAPI, Flask, or similar frameworks

Experience building frontend applications using React.js or similar frameworks

Experience designing and shipping APIs, internal tools, and product workflows

Strong debugging skills and the ability to work through ambiguous engineering problems

Product mindset - you care about the user outcome, not just the code

Strongly Preferred

Hands-on experience with AWS, FastAPI and NextJS

Experience building AI-powered product features using LLM APIs and modern AI tooling

Familiarity with orchestration frameworks such as LangChain, LangGraph, or similar workflow frameworks

Experience building agentic systems, tool-calling workflows, or multi-step AI applications

Experience with vector databases, retrieval pipelines, embeddings, and knowledge systems

Experience with async systems, queues, background jobs, and event-driven architectures

Familiarity with Docker and production deployment practices

Experience working with data pipelines and large-scale processing systems

Bonus Points

Experience in SEO, search, web intelligence, crawling, or content systems

Experience with evaluation frameworks for AI systems

Experience with prompt engineering, guardrails, output validation, and fallback design

Experience with observability tools, system monitoring, and production debugging

Familiarity with MLOps or workflow orchestration tools

Experience building 0→1 internal tools, automation products, or AI copilots

What Success Looks Like

In this role, success means you can:

ship AI-native product features quickly and reliably

build workflows that combine models, tools, and data into real customer value

improve the performance and robustness of our AI systems over time

operate comfortably across backend, frontend, AI orchestration, and AWS infrastructure

think like an owner and help shape both product direction and technical execution

Who You Are

You are highly curious and learn new tools fast

You like building useful systems, not just prototypes

You are excited by AI tooling, agentic software, and workflow automation

You are comfortable moving across layers of the stack

You care about product quality, speed, and practical impact

You take ownership and enjoy solving real-world engineering problems

Why Join VisibilityStack.ai

VisibilityStack was founded by the Founders of FirstPrinciples ($8m+ ARR) and Listnr.ai (3.5mn+ users across 200 countries) to solve for one of the painful problems to exist in this decade - search visibility.

As product, user, content discovery moves to Generative search, we aim to provide the best tools to help businesses get discovered on AI chatbots. We're at the forefront of the AI space with a team thats been building in AI since 2018, way before GenAI became a buzzword.

At VS, you'll get a chance to work on an AI-native product in one of the fastest-changing categories in software.

Build at the frontier of SEO, GEO, AI search, and agentic discovery.

Ship real product, that will be used by millions of users.

Get broad ownership across product, engineering, AI systems, and infrastructure.

Be part of a fast-moving team building software that directly impacts customer growth