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
