Founding Context Engineer (AI Infrastructure)

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Title of the role:Founding Context Engineer (AI Infrastructure)

Location: New York City (On-site)

Company Stage of Funding: Pre-Seed ($3.3M), Early Product-Market Fit

Office Type: Onsite

Salary: $140,000 – $220,000 + Equity

Company Description

We’re representing a pre-seed startup building the infrastructure layer for modern go-to-market (GTM) systems. Their vision is to create “ambient automation” — systems that understand business context and execute intelligently without manual orchestration.

They is building a universal API for B2B businesses, replacing fragmented integrations across dozens of tools with a unified Context API. Their platform enables AI systems to access, reason over, and act on structured business context reliably — solving one of the core limitations of today’s AI systems.

Backed by top investors and a small, senior team from companies like Uber, Lyft, and Capchase, this company is tackling foundational problems in data infrastructure, semantic modeling, and AI-native system design. This is a ground-floor opportunity to define entirely new paradigms in how AI interacts with enterprise data.

What You Will Do

As a Founding Context Engineer, you will build the core infrastructure layer that enables AI systems to reliably access and reason over business context in production.

Key responsibilities include:

• Design and build our Context Management API, enabling structured context across workflows
• Develop new data access patterns that move beyond SQL toward semantic querying for AI systems
• Build retrieval and reasoning pipelines that understand business context before querying data
• Architect self-healing data models that automatically improve based on usage and feedback
• Develop semantic modeling infrastructure that translates business questions into precise, verifiable queries
• Build systems for identity resolution and data unification across dozens of enterprise tools
• Design knowledge graphs and context systems that evolve as business data changes
• Work closely with founders and customers to iterate rapidly on core infrastructure and product direction

Ideal Background

• 3+ years of experience building production systems
• Experience working with LLMs, retrieval systems, embeddings, or vector databases
• Familiarity with knowledge graphs or semantic data systems
• Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex) or multi-agent systems
• Strong understanding of data infrastructure, including data warehouses (Snowflake, BigQuery) and semantic layers (dbt)
• Experience building or working with production ML systems (monitoring, evaluation, versioning)
• Strong backend engineering skills in Python or similar languages
• Comfortable working in fast-moving, ambiguous, zero-to-one environments

Preferred

• Experience with enterprise data systems (Salesforce, Segment, HubSpot, Gong, etc.)
• Familiarity with workflow orchestration tools (Airflow, Prefect)
• Experience with graph databases or advanced knowledge graph systems
• Experience building real-time data pipelines or streaming systems
• Exposure to multi-agent systems (LangGraph, CrewAI)
• Experience working with reverse ETL tools or data activation platforms

Compensation and Benefits and Other Things

• Base Salary: $140K – $220K
• Equity: Meaningful early-stage equity
• Work Setup: Onsite in New York City

Additional Highlights:

• Founding engineer role (engineer #5–6) with direct impact on company trajectory
• Work directly with experienced founders and early customers
• Opportunity to define new paradigms in AI + data infrastructure
• High ownership, rapid iteration, and first-principles engineering culture