Principal Engineer, API & MCP Platform
Listed on 2026-06-06
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IT/Tech
AI Engineer
Babel Street is the trusted technology partner for the world’s most advanced identity intelligence and risk operations. We deliver advanced AI and data analytics solutions providing unmatched, analysis-ready data regardless of language, proactive risk identification, 360‑degree insights, high-speed automation, and seamless integration into existing systems. Babel Street empowers governments and commercial organizations to transform high‑stakes identity and risk operations into a strategic advantage.
The actionable insights we deliver safeguard lives and protect critical assets around the world. Babel Street is headquartered in Reston, Virginia, with regional offices in Boston, MA and Cleveland, OH, and international offices in Australia, Canada, Israel, Japan, and the U.K.
We are seeking a Principal Engineer to lead Babel Street’s API and MCP platform strategy and delivery as we evolve toward an AI‑native, agent‑driven platform.
This hands‑on, senior technical leadership role is responsible for defining and delivering API‑first platform capabilities that enable both developers and AI agents to interact with Babel Street’s services. You will lead the design and implementation of semantic APIs, Model Context Protocol (MCP) integrations, and context‑aware service patterns that power next‑generation intelligence workflows.
The role requires a finger‑on‑keyboard engineer who can both define direction and deliver foundational systems. You will partner closely with AI, Data, and Platform teams to ensure Babel Street’s APIs and services are consistent, discoverable, scalable, and optimized for agentic workflows.
You will work in close partnership with the Architecture function to align on long‑term technical direction, ensuring API and MCP platform decisions are consistent with the company’s broader architectural vision while maintaining a strong focus on execution and delivery.
This is a hybrid role working out of either our Reston, VA or Somerville, MA office. Full remote may be considered.
Why This Role MattersThis role will be instrumental to Babel Street’s AI‑native technology strategy. The API and MCP platform will serve as the interface layer between data, AI, and product capabilities, enabling agents, developers, and systems to interact seamlessly.
This is a high‑impact, senior technical leadership role with broad influence across the organization and the opportunity to shape the future of Babel Street’s platform. The position spans four core domains:
MCP & Agent IntegrationYou will lead Babel Street’s Model Context Protocol (MCP) strategy and implementation, enabling agents and AI systems to interact with services in a standardized and scalable way. This includes defining patterns for:
- Tool and service discovery
- Agent‑to‑service communication
- Context‑aware interactions
You will partner closely with AI and platform teams to enable agent‑native workflows across the organization.
Semantic APIs & Agent‑Ready InterfacesYou will lead the design of semantic, agent‑friendly APIs, where documentation becomes a first‑class interface for AI‑driven systems. This includes defining standards for:
- API descriptions optimized for agents
- Schema consistency and semantic modeling
- Tool and service discoverability
- API documentation optimized for agent consumption
You will establish best practices for documentation‑as‑code, ensuring APIs are designed for both developers and AI systems.
Context Management & Runtime PatternsYou will define patterns for context‑aware APIs and services, including:
- Context management and retrieval
- Context caching
- Session and state management
- Memory‑aware service interactions
You will help design scalable context‑aware systems leveraging technologies such as Vertex AI Context Caching and related frameworks.
Key Responsibilities- Partner closely with Architecture to define and lead Babel Street’s API and MCP platform strategy
- Design and deliver semantic, agent‑ready APIs
- Establish MCP standards and implementation patterns
Define context management patterns for agent workflows - Partner with AI and Data teams to enable agent‑native architectures
- Establish API governance and platform standards
- Build…
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