Sr. Director of Engineering - API

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

• Define and lead Babel Street’s API-first platform strategy.
• Establish consistent patterns for service design, versioning, discoverability, and governance.
• Evolve the platform toward agent-ready APIs, ensuring services are consumable by both human developers and AI agents.
• Establish standards for API consistency, reliability, and performance across the organization.
• Work closely with product and engineering teams to ensure APIs are designed as first-class platform capabilities.

MCP & Agent Integration

• Lead Babel Street’s Model Context Protocol (MCP) strategy and implementation.
• Define patterns for:
  • MCP service exposure
  • Tool and service discovery
  • Agent-to-service communication
  • Context-aware interactions
• Partner closely with AI and platform teams to enable agent-native workflows.

Semantic APIs & Agent-Ready Interfaces

• Lead the design of semantic, agent-friendly APIs.
• Define standards for:
  • API descriptions optimized for agents
  • Schema consistency and semantic modeling
  • Tool and service discoverability
  • API documentation optimized for agent consumption
• Establish best practices for documentation-as-code.

Context Management & Runtime Patterns

• Define patterns for context-aware APIs and services, including:
  • Context management and retrieval
  • Context caching
  • Session and state management
  • Memory-aware service interactions
• Help design scalable context-aware systems leveraging technologies such as Vertex AI Context Caching.

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 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.

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.