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We are hiring

Come build the layer underneath

Two openings. Both on-site in the New York metro, both working on the platform our clients run their operations on.

Why here

Most engineering jobs put you three layers away from the person who has the problem. Ours does not. You will sit near the people who talk to clients, and you will hear the requirement change before it becomes a ticket.

The work is a permissioned, multi-tenant platform that mid-market companies run their operations on. Roles and access groups, single sign-on, an API with row and column-level control, MCP servers that agents plug into, and the applications built on top of all of it. It has been in production for ten years and it is being extended into AI-native territory right now: knowledge graph construction, LLM-powered entity resolution, agent-driven query layers.

That combination is unusual. Most places offer you a mature system to maintain or a greenfield one to gamble on. This is a mature system with a genuinely new problem on top of it.

How we work

On-site, five days a week. We are direct about this because it filters, and it should. We also offer unlimited paid time off, and those two things are not in tension: we are not counting hours, we are saying that engineers and business people arriving at a shared understanding of a client's problem happens in a room.

You will use AI, and you will be expected to understand what it produced. The gap between people who can generate working code and people who understand why it works has never been wider. We hire for the second thing. AI assistants are force multipliers here and we use them daily, but the fundamentals underneath are what we interview on.

Six years of experience, and we mean it. Both roles ask for battle-tested fundamentals. We would rather hire one person who has debugged a production database at 2am than three who have not.

If that sounds like the place you have been looking for, the roles are below.

The roles

SQL / Data specialization

Data Engineer

PostgreSQLPythonAirflow

We are seeking a seasoned Data Engineer who brings deep, hands-on expertise in SQL and relational database systems. The ideal candidate developed their craft over at least 6 years, possessing battle-tested fundamentals in query design, schema architecture, and performance tuning. While the role centers on SQL and data infrastructure, we expect a full-stack awareness; someone who understands how data flows from ingestion through transformation to consumption and can collaborate credibly across the entire engineering stack. You will help architect an AI-native platform that includes knowledge graph construction, LLM-powered entity resolution, and agent-driven query layers.

Education
4 year undergraduate degree
Experience
6+ years
Location
Hoboken, NJ metro area
Work model
On-site, 5 days per week
Classification
Full-stack mindset; SQL / data specialization

Technical core

  • Advanced SQL mastery — Window functions, CTEs (recursive and non-recursive), subquery optimization, set-based logic, complex joins, and dynamic SQL.
  • Query performance engineering — Execution plan analysis (EXPLAIN / EXPLAIN ANALYZE), indexing, partitioning, query rewrites, and statistics-driven tuning.
  • Database administration — Backup and restore strategies, replication, connection pooling, vacuum tuning, role-based access control, and disaster recovery planning.
  • ETL/ELT pipeline development — Hands-on experience designing, building, and maintaining production-grade data pipelines using modern orchestration and transformation tooling.

Database technologies

  • PostgreSQL — Strongly preferred. PL/pgSQL stored procedures, triggers, materialized views, JSONB querying, full-text search, extensions ecosystem.
  • Additional RDBMS — Microsoft SQL Server (T-SQL, SSMS, SSIS, SSRS, SSAS), MySQL/MariaDB, or Oracle PL/SQL experience is a plus.
  • Cloud data platforms — Familiarity with Snowflake, Google BigQuery, Amazon Redshift, or Azure Synapse Analytics.

Tooling and infrastructure

  • Orchestration — Apache Airflow or Prefect for DAG-based workflow orchestration and scheduling.
  • Python — pandas, SQLAlchemy, psycopg2/asyncpg, Alembic for migrations, Great Expectations for data quality.
  • Scripting — Bash and shell scripting for automation and cron-based workflows.
  • DevOps — Git version control (GitHub/GitLab), CI/CD for data pipelines (Azure DevOps), Docker and containerized database environments.

AI, graph and knowledge engineering

  • Graph databases — Experience or strong familiarity with Neo4j, Apache AGE, or similar. Proficiency in Cypher or Gremlin, and understanding of graph modeling, entity resolution, and relationship traversal.
  • LLM integration — Practical exposure to integrating large language models into data pipelines: prompt engineering, retrieval-augmented generation, and orchestrating LLM-powered entity extraction and classification.
  • Vector and embedding infrastructure — Familiarity with vector databases (pgvector, Pinecone, Weaviate) and embedding-based search for semantic retrieval and similarity matching.
  • Agent frameworks — Awareness of agentic frameworks (LangChain, LlamaIndex, Semantic Kernel) and how they connect to underlying data infrastructure is a strong plus.

Visualization and business intelligence

  • Tableau — Nice to have. Connecting live and extract data sources, calculated fields, LOD expressions, dashboard design, Tableau Server/Cloud publishing, and performance optimization.

Attributes

  • Years of building complex queries and data models
  • Comfortable working cross-functionally with front-end engineers and analysts
  • Clear communicator who can translate complex data concepts for non-technical stakeholders
  • Interest in emerging data technologies: real-time streaming (Kafka, Flink), vector databases, or data mesh architectures

Attach your resume to the email.

JavaScript / front-end specialization

Front-End Engineer

JavaScriptTypeScriptD3.js

We are looking for an accomplished Front-End Engineer whose JavaScript expertise rests on a deep, instinctive understanding of vanilla JavaScript. While the role focuses on front-end delivery, we expect a full-stack sensibility: understanding APIs, data flow, build systems, and deployment well enough to collaborate effectively with back-end and data engineers. This role sits at the intersection of design and AI-native architecture. You will build interfaces that surface insights from knowledge graphs, integrate LLM-driven query layers, and render complex, agent-powered workflows in intuitive ways.

Education
4 year undergraduate degree
Experience
6+ years
Location
Hoboken, NJ metro area
Work model
On-site, 5 days per week
Classification
Full-stack mindset; JavaScript / front-end specialization

CSS architecture

  • Preprocessors and CSS-in-JS — SCSS/SASS, PostCSS, or CSS-in-JS (Styled Components, Emotion).
  • Utility-first CSS — Tailwind CSS for rapid prototyping.

Testing and quality

  • Unit testing — Jest, Jasmine, or Vitest with comprehensive coverage.
  • End-to-end testing — Cypress, Playwright, or Selenium/WebDriverIO.
  • Component testing — Testing Library, and Storybook for visual regression.
  • Linting and formatting — ESLint with TypeScript configs, Prettier, Husky pre-commit hooks.

Tooling and infrastructure

  • DevOps — Git workflows and CI/CD pipelines with Azure DevOps.
  • Containerization — Docker for containerized front-end builds.
  • Design collaboration — Figma or Sketch for design handoff, and the ability to translate designs to pixel-perfect implementation.
  • Design systems — Building and maintaining reusable component libraries.

AI and intelligent interfaces

  • LLM-powered UI patterns — Experience or strong interest in conversational interfaces, streaming LLM response rendering, and chat-based UX that integrates with back-end AI services.
  • Knowledge graph visualization — Comfort rendering graph-based data structures, entity relationship maps, and interactive node-edge visualizations using D3.js, Cytoscape.js, or similar.
  • Agent-driven workflows — Familiarity with front-end experiences that orchestrate or surface results from autonomous agent pipelines, including progress indicators, multi-step task flows, and human-in-the-loop review interfaces.
  • AI-assisted development — Demonstrated use of AI coding assistants as force multipliers in day-to-day development is a strong plus.

Visualization and business intelligence

  • Tableau — Nice to have. Embedding Tableau dashboards via the JavaScript API, configuring interactive filters, and integrating visualizations into web applications.
  • Charting libraries — Exposure to D3.js, Chart.js, Plotly, AG Grid, or Apache ECharts for custom data visualization is a plus.

Attributes

  • Can build complex UIs from scratch, with CSS, list pagination, action filtering, and advanced charting
  • Passionate about user experience, interface polish, and animation
  • Strong debugging instincts; comfortable in DevTools profiling memory, network, and rendering performance
  • Understands back-end fundamentals (REST, authentication, databases) well enough to have productive architectural conversations
  • Experience with front-end frameworks such as Angular, React, or Vue.js

Attach your resume to the email.

Not quite a fit?

If neither role matches but you think you would belong here, write to us anyway. We would rather hear from a good engineer at the wrong moment than not hear from them at all.

Email Alex directly

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