Principal Engineer, API & MCP Platform

country: US all locations: [Reston, VA OR Somerville, MA] commitment: Full Time department: Featured Hatch Accounts location: Reston, VA OR Somerville, MA team: Babel Street Why this role matters:: This 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:  API Platform & Strategy  You will define and lead Babel Street’s API-first platform strategy, establishing consistent patterns for service design, versioning, discoverability, and governance.  You will help evolve the platform toward agent-ready APIs, ensuring services are consumable by both human developers and AI agents. You will establish standards for API consistency, reliability, and performance across the organization.  You will also work closely with product and engineering teams to ensure APIs are designed as first-class platform capabilities, not just service interfaces.  MCP & Agent Integration  You 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:  MCP service exposure  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 Interfaces  You 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 Patterns  You 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.  What you will do:: 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 foundational frameworks and reusable components   Provide hands-on technical leadership and mentorship   Partner with Google and other vendors on platform capabilities   Drive adoption of API and MCP standards across engineering teams   What you will bring:: Required Qualifications  10+ years of software engineering experience  Experience operating at Principal Engineer or Staff+ level  Strong hands-on experience building distributed systems   Experience designing and building API-first platforms  Experience with cloud-native architectures (GCP preferred)   Experience building developer platforms or service-oriented architectures   Strong system design and architectural thinking skills  Proven ability to lead cross-team technical initiatives   Preferred Qualifications  Hands-on work with Google Cloud Platform (GCP)  Familiarity with Vertex AI Agent Engine   Background in ADK and reasoning frameworks such as LangChain  Understanding of the Model Context Protocol (MCP)   Exposure to data warehouse technologies like BigQuery and Snowflake  Knowledge of Apigee or similar API gateway solutions   Proven ability to design semantic APIs for AI or agent-driven use cases   Experience managing context or building memory systems   Development of agent-based architectures or orchestration frameworks   Exposure to Anti-Gravity  What success looks like:: 30 Days  Assess current API and platform architecture  Define API and MCP platform strategy   Identify early opportunities for standardization   60 Days  Deliver initial platform frameworks and standards  Begin rollout of semantic API patterns   Establish MCP integration approach   90 Days  Agent-ready APIs in production  MCP-enabled services deployed Clear platform standards adopted across teams Measurable improvement in API consistency and developer velocity