Senior Full Stack AI Engineer

About Us

VisibilityStack.ai is an agentic AI platform that automates organic growth across AI & Traditional Search through AI Agents augmented with deep human expertise. While others stop at scores, our agents execute autonomously by managing technical AISO, citations, entity optimization, and content intelligence workflows.VisibilityStack helps companies monitor, analyze, and improve their visibility across:

AI search engines

generative answer engines

traditional search

LLM-powered discovery surfaces

agentic research and recommendation workflows

Our product sits at the intersection of AI search, SEO/GEO, large-scale data systems, applied AI infrastructure, workflow automation, and modern SaaS product engineering.

We care about building fast, but not fragile. We ship quickly, maintain high engineering standards, and turn cutting-edge AI capabilities into reliable product experiences customers can use every day.

The Role

We are looking for a Senior Software Development Engineer who can own complex product and infrastructure problems end to end. This is a senior engineering role across backend systems, AI workflows, data infrastructure, cloud architecture, and product surfaces. You will work closely with product, engineering, and leadership to design and ship core systems behind VisibilityStack.ai. You should be comfortable operating across the stack, but your strength should be in building reliable, scalable, production-grade systems.You will help build the intelligence layer behind the product: systems that collect data, run AI workflows, orchestrate agents, generate insights, power recommendations, and turn messy real-world search visibility problems into clean customer-facing product experiences. This role is ideal for someone who has strong engineering fundamentals, has shipped production systems before, understands cloud-native architecture, and is excited about building AI-native software from 0 to 1.

What You’ll Work On

1. Build AI-native product workflows: You will design and ship product features powered by LLMs, retrieval systems, workflow engines, and agentic software.

This includes:

Building systems for SEO/GEO research, content intelligence, brand monitoring, query expansion, and recommendation generation

Designing AI workflows that combine models, tools, APIs, databases, and external data sources

Building production-grade workflows with retries, fallbacks, validation, observability, and human-in-the-loop controls

Creating internal tools for prompt iteration, evaluation, debugging, and rapid experimentation

Turning AI prototypes into reliable product features customers can use every day

2. Own backend systems and APIs: You will build the backend services that power VisibilityStack’s core product workflows.

This includes:

Designing and building scalable APIs using Python, FastAPI, or similar frameworks

Building services for crawling, ingestion, processing, scoring, analysis, and recommendations

Designing clean service boundaries, data models, and internal abstractions

Working with async systems, queues, background jobs, and event-driven architecture

Improving performance, reliability, security, and maintainability across backend systems

3. Build agentic orchestration layers: You will help build the orchestration layer that allows AI systems to reason, act, retrieve, validate, and improve over time.

This includes:

Designing multi-step AI workflows with state management, memory, tool use, and context handling

Building integrations between AI systems, internal services, external APIs, databases, and web intelligence sources

Implementing retrieval pipelines using embeddings, vector databases, document processing, and knowledge systems

Building systems to evaluate AI outputs, monitor agent behavior, and debug workflow failures

Improving reliability, cost, latency, and accuracy of AI-driven workflows

4. Build data and intelligence infrastructure: VisibilityStack is a data-heavy product. You will help build the systems that turn raw search, content, web, and brand data into useful product intelligence.

This includes:

Building ingestion pipelines for structured and unstructured data

Working on crawling, parsing, extraction, ranking, classification, and summarization systems

Designing systems that process web-scale or large-volume data reliably

Building data models that support monitoring, scoring, benchmarking, and insight generation

Collaborating on systems that turn raw data into actionable recommendations for customers

5. Build product surfaces and internal tools: While this is not a pure frontend role, you should be comfortable building or contributing to product interfaces when needed.

This includes:

Building customer-facing dashboards and product workflows using React, Next.js, or similar frameworks

Creating internal operator tools for monitoring, debugging, and workflow control

Working closely with product/design to ship usable, fast, polished interfaces

Translating complex backend and AI workflows into simple product experiences

6. Own AWS infrastructure and production deployment: You will help build and manage the cloud infrastructure that powers the product.

This includes:

Building and deploying services on AWS

Working with cloud-native compute, storage, queues, databases, containers, and observability tools

Supporting containerized services and deployment pipelines

Improving system performance, scalability, reliability, and cost efficiency

Helping define engineering best practices around monitoring, alerting, infrastructure hygiene, and production operations

7. Raise engineering quality and velocity: As a senior engineer, you will be expected to improve the quality of both the product and the engineering culture.

This includes:

Leading technical design for important systems

Making strong architecture decisions with clear tradeoffs

Writing clean, maintainable, well-tested code

Reviewing code and helping other engineers improve

Debugging hard production issues

Moving fast without creating unnecessary technical debt

Bringing ownership, urgency, and high standards to the team

What We’re Looking For

Core Requirements

4+ years of software engineering experience

Strong backend engineering experience with production systems

Strong proficiency in Python

Experience building APIs and backend services using FastAPI, Flask, Django, or similar frameworks

Experience with React, Next.js, or similar frontend frameworks

Strong understanding of system design, data structures, algorithms, databases, and distributed systems

Experience designing and shipping production APIs, internal tools, data workflows, and customer-facing features

Strong debugging ability across backend, frontend, cloud, and data systems

Experience working with AWS or similar cloud platforms

Ability to work independently on ambiguous problems and drive them to completion

Product mindset: you care about the customer outcome, not just the code

Strongly Preferred

Hands-on experience with AWS, FastAPI, and Next.js

Experience building AI-powered product features using LLM APIs

Experience with LangChain, LangGraph, or similar orchestration frameworks

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

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

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

Experience with Docker and production deployment workflows

Experience building data pipelines or large-scale processing systems

Experience improving reliability, latency, cost, and observability in production systems

Bonus Points

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

Experience with AI evaluation frameworks

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

Experience with observability tools, monitoring systems, and production debugging

Familiarity with MLOps or workflow orchestration tools

Experience building 0 to 1 products, internal platforms, automation systems, or AI copilots

Prior startup experience or experience working in fast-moving product teams

What Success Looks Like

In this role, success means you can:

Own major product and infrastructure systems end to end

Ship AI-native product features quickly and reliably

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

Improve the robustness, speed, cost, and accuracy of our AI systems over time

Operate comfortably across backend, AI orchestration, data infrastructure, frontend, and AWS

Make good technical decisions under ambiguity

Help shape both product direction and technical execution

Raise the engineering bar for the team

Who You Are

You are a builder.

You like taking messy, ambiguous problems and turning them into clean, working systems.

You care about speed, but you also care about reliability. You are excited by AI tooling, agentic software, search, automation, and workflow-driven products.

You do not need perfect specs to start. You can think from first principles, make reasonable tradeoffs, and move projects forward.

You enjoy working across layers of the stack and are comfortable owning outcomes, not just tickets.

Why Join VisibilityStack.ai

Search is changing faster than it has in the last two decades

As product discovery, content discovery, and brand discovery move from traditional search engines to AI-native interfaces, companies will need a new category of tools to understand and improve their visibility

VisibilityStack is building that category

At VisibilityStack, you will get the chance to:

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

Work on an AI-native product in one of the fastest-changing software categories

Own important product and infrastructure problems from day one

Build systems that directly impact customer growth

Work with founders who have built and scaled products used by millions of users

Ship real product, not demos

We are looking for someone who wants ownership, speed, and meaningful technical problems

If you want to build serious AI-native software in a category that is being rewritten in real time, this is the role