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

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 deplo
• yment
• 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

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