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 Youll 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 VisibilityStacks 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 .