Founding Context Engineer (AI Infrastructure)

Founding Context Engineer

Location: New York City
Company Stage: Seed / Pre-Series A — AI Infrastructure & Enterprise Data Systems
Office Type: On-site
Salary: $140K – $220K + Meaningful Equity

Company Description

We’re partnering with an early-stage AI infrastructure startup building the context layer that powers the next generation of enterprise AI systems. Their platform acts as a universal API across business systems, enabling AI agents to reason over structured enterprise context, orchestrate workflows, and execute actions reliably across complex GTM and operational environments.

The company is building foundational infrastructure for semantic querying, self-healing data systems, and context-aware AI workflows that replace fragmented integrations and brittle automation layers. Backed by leading early-stage investors and led by a highly technical founding team from top technology and enterprise software companies, they are rapidly scaling product and engineering capabilities in NYC.

What You Will Do

• Design and build structured context management systems for AI agents operating across enterprise workflows


• Develop semantic retrieval pipelines and knowledge systems that improve AI reasoning and decision-making


• Build context-aware APIs and orchestration layers that connect AI systems with enterprise data sources


• Architect self-healing data models and feedback systems that continuously improve context accuracy over time


• Design semantic query interfaces and abstractions beyond traditional SQL-based workflows


• Develop systems for identity resolution and entity mapping across dozens of enterprise integrations


• Build scalable infrastructure for embeddings, vector search, knowledge graphs, and multi-agent workflows


• Work closely with customers and internal teams to solve complex context-engineering problems in production


• Contribute to rapid iteration cycles in a highly technical, research-oriented startup environment


• Help shape foundational architecture decisions across AI infrastructure, retrieval systems, and semantic modeling

Ideal Background

• 3+ years building production-grade software systems in fast-paced environments


• Experience with retrieval systems, embeddings, vector databases, knowledge graphs, or LLM-powered applications


• Strong understanding of production ML systems, including evaluation, monitoring, and versioning workflows


• Experience with LLM orchestration frameworks or multi-agent systems


• Familiarity with enterprise data systems, semantic layers, or modern data infrastructure


• Strong backend engineering fundamentals with experience building scalable distributed systems


• Ability to work across ambiguity and solve novel technical problems from first principles


• Strong product intuition and systems thinking mindset


• Excellent communication skills and ability to collaborate closely across engineering and customer-facing workflows

Preferred

• Experience working with enterprise data warehouses and GTM tooling ecosystems


• Familiarity with knowledge graphs, graph databases, or semantic modeling infrastructure


• Experience with workflow orchestration frameworks and real-time data pipelines


• Background building AI infrastructure products, developer platforms, or agentic systems


• Experience working in high-ownership startup environments with rapid iteration cycles


• Exposure to streaming systems, event-driven architectures, or reverse ETL workflows

Compensation and Benefits

• Base salary: $140K – $220K


• Significant early-stage equity package


• Opportunity to join as one of the earliest engineers with major ownership and technical influence


• Collaborative, highly technical, and fast-moving engineering culture


• Direct exposure to customers and product strategy


• Strong focus on AI infrastructure, semantic systems, and next-generation enterprise AI tooling


• In-person NYC environment with quarterly off-sites and rapid product iteration cadence