Senior Full Stack AI Engineer

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