Principal Full Stack Engineer

Location: Remote 

Type: Part-time to full-time

About the Company

We are building a next-generation intelligence platform that transforms complex, fragmented data into structured, actionable insights. Our system combines advanced graph modeling, distributed data pipelines, and applied AI to unlock relationships, patterns, and narratives at scale. We operate at the intersection of data infrastructure, machine learning, and user-facing applications, with a focus on turning unstructured inputs into deeply connected knowledge systems.

The platform is a modular architecture spanning data ingestion pipelines, normalization layers, graph-based storage, and advanced retrieval systems. We are developing agent-driven workflows where specialized AI systems collaborate across ingestion, validation, analysis, and generation, producing insights, evaluations, and narrative outputs from previously unstructured information.

We operate at the intersection of data infrastructure, machine learning, and applied AI, combining knowledge graphs, LLM-powered reasoning, and multi-agent orchestration to unlock patterns and connections at scale. The company was started by a second time founder and is going after hard problems with meaningful customer value. 

About the Role

We are looking  the kind of engineer who naturally becomes the technical backbone of a small company. You don’t get blocked by uncertainty. You can zoom out to define the right system, then zoom in and implement it yourself. You know when to move fast, when to go deep, and how to keep shipping while the product is still evolving. 

This is a hands-on builder role for someone as comfortable defining the architecture of an agentic workflow as they are reviewing the production code that runs it. You will work at the intersection of LLMs, graph data, media automation, infrastructure and real customer problems, turning emerging AI capabilities into features people rely on every day.

We are an early-stage team. We have a beta environment built with infrastructure as code and early features, but requires moderate updating and debugging on front and backends. There is no committee, just agile sprint standups and a backlog grooming session between 3-4 individuals. You will own systems end-to-end, set the technical standards, and ship. If your best work happens when the surface area is wide and the team is small, this is your environment.

What You'll Do

• Design, build, and ship customer-facing AI-powered features  from onboarding through checkout, owning quality and reliability end-to-end
• Architect and implement agentic workflows, LLM pipelines, and GraphRAG systems that surface faster, more accurate insights for users
• Build and operate agent swarms: multi-agent systems that collaborate, hand off work, self-correct, and produce real outputs with minimal human-in-the-loop to accelerate development efficiency 
• Own the frontend architecture: React, Vite, TypeScript, TanStack Router/Query, Tailwind, shadcn/ui
• Own the backend architecture: Python, FastAPI, PydanticAI, CopilotKit
• Design and build data ingestion pipelines for messy real-world formats  - db files, PDFs, images
• Model and query complex graph data in Neo4j; optimize PostgreSQL at scale
• Build confidence scoring, deduplication, conflict detection, and verification engines
• Implement graph visualization interactions via ReactFlow, GoJS and DAG-based data trees
• Orchestrate agentic coding and data workflows: designing, running, and managing multi-agent systems that generate, review, test, and iterate autonomously
• Use AI-native development tools (Claude Code or equivalent) as a core part of your workflow  and push the boundary of what they can do
• Own system reliability, observability, and performance post-launch

Required Skills and Experience

• 10+ years of full-stack engineering with real end-to-end ownership
• Track record of building and shipping multi-service or distributed systems in production
• Strong product instinct and the ability to convert ambiguous customer input into working software
• Clear evidence that you’ve taken important features from zero to production quickly
• Strong Python backend skills, including FastAPI and modern typed application patterns
• Strong frontend skills with React, TypeScript, and modern UI tooling
• Experience building AI-native systems, including multi-agent or agent-orchestrated workflows in production
• Strong data modeling instincts, especially around graph-shaped or highly relational data
• Experience working with inconsistent, messy, real-world inputs and ingestion pipelines
• Comfort owning infrastructure in AWS and operating directly in production environments
• Experience being the primary technical decision-maker on a very small team
• High agency, strong judgment, low ego, and a visible sense of urgency

Strong preference for people who

• Have built with LangGraph, CrewAI, AutoGen, PydanticAI, or equivalent orchestration frameworks
• Have worked with Neo4j and PostgreSQL in systems where the data model actually matters
• Use AI coding tools as a core part of how they work, not as an occasional convenience
• Can move fluidly between product, engineering, and execution without needing heavy process
• Know how to ship fast without becoming sloppy
• Have team attitude and culture - we win together as one team.

Our Tech Stack

FastAPI / Python, PydanticAI, React, TypeScript, Vite, TanStack, Tailwind, shadcn/ui, Neo4j, PostgreSQL, Claude and multi-modal, FAL.ai, Remotion, AWS

Nice to Have

• GoJS or other graph visualization libraries
• GEDCOM or genealogy/records data formats
• FAL.ai, Remotion, or comparable media generation tools
• Experience with LLM evaluation frameworks and production observability for AI systems

This role is probably a fit if you

• Want CTO-level ownership without being boxed into a pure management job
• Like operating with a wide surface area and a small, fast team
• Prefer building real systems over debating them
• Are energized by ambiguity, velocity, and customer-driven iteration
• Can hold a high technical bar while still shipping

This role is probably not a fit if you

• Need highly defined tickets and heavy process to be effective
• Prefer to specialize narrowly rather than own the whole product
• Get stuck when requirements are incomplete
• Like architecture more than delivery

Candidates considered for this role may be asked to provide two professional references prior to any offer of employment.

We are committed to equal employment opportunity and embrace diversity. Hiring decisions are made on merit, without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, age, marital status, veteran status, disability status, or any other protected category under applicable law.