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.
- 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
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
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