Senior AI Integration Engineer

We're looking for a Senior Integration Engineer to build high-performance, secure, and production-grade API layers, custom Model Context Protocol (MCP) servers, and real-time data delivery services optimized for both human applications and autonomous AI agents. This role requires experience operating at high throughput — thousands of requests per second — and building integration layers that AI agents rely on directly.

We're looking for a Senior Integration Engineer to build high-performance, secure, and production-grade API layers, custom Model Context Protocol (MCP) servers, and real-time data delivery services optimized for both human applications and autonomo...

Must-Have

• Overall Experience: 8+ years in Backend Software Engineering, Distributed Systems Architecture, or Enterprise Platform Engineering
• Resiliency Engineering: 4+ years architecting mission-critical systems requiring "four-nines" (99.99%) availability, rigorous traffic shaping, and self-healing systems
• AI & Agentic Systems: 2+ years building production-grade integration layers, semantic context gateways, or RAG endpoints consumed by LLMs and autonomous AI agents
• Proficiency in Advanced API Design & Context Optimization
• Production-level proficiency in one or more of: C# (.NET Core), Java, Python, or Node.js/TypeScript
• Proficiency in Enterprise Scalability & Traffic Management
• Proficiency in Lock & Contention Mitigation (API & Database Tier)
• Proficiency in Hardened Security, Governance & AI Isolation

Preferred Experience

• GraphQL and dynamic JSON/gRPC filtering layers (zero-waste data fetching)
• Custom MCP server development for LLM context exposure
• Heterogeneous schema merging for LLM tool-calling (e.g., relational DBs, analytics platforms like Pendo/Hotjar, observability tools)
• Semantic token-aware API pagination and streaming
• Context-aware gateways for conditional object graph hydration based on agent intent
• Edge performance: CloudFront Functions, Lambda@Edge, HTTP/3, WebSockets
• PostgreSQL and OpenSearch/Elasticsearch access layers with sub-millisecond caching
• Reactive streams and rate-limiting for Amazon MSK (Kafka), SQS, and HTTP endpoints
• Circuit Breakers, Bulkheads, and Retry-with-Exponential-Backoff (Polly, Resilience4j, or equivalent)
• Amazon MemoryDB / Redis OSS / Valkey for rate limiters, session caches, and semantic query caching
• Optimistic Concurrency Control (OCC) via eTags/versions; Pessimistic Locking only where strictly necessary
• CQRS separating high-volume writes from intensive read queries in PostgreSQL
• Asynchronous write delegation for high-contention API writes to Kafka/MSK
• Zero Trust security: OAuth2, OIDC, mTLS, and AWS Lake Formation
• Security proxy layers over Amazon Bedrock (prompt injection filtering, PII redaction, API token quota enforcement)
• End-to-end API runtime tracing with OpenTelemetry (oTel) and Datadog

We're looking for a Senior Integration Engineer to build high-performance, secure, and production-grade API layers, custom Model Context Protocol (MCP) servers, and real-time data delivery services optimized for both human applications and autonomous AI agents. This role requires experience operating at high throughput — thousands of requests per second — and building integration layers that AI agents rely on directly.

We're looking for a Senior Integration Engineer to build high-performance, secure, and production-grade API layers, custom Model Context Protocol (MCP) servers, and real-time data delivery services optimized for both human applications and autonomo...

Must-Have

• Overall Experience: 8+ years in Backend Software Engineering, Distributed Systems Architecture, or Enterprise Platform Engineering
• Resiliency Engineering: 4+ years architecting mission-critical systems requiring "four-nines" (99.99%) availability, rigorous traffic shaping, and self-healing systems
• AI & Agentic Systems: 2+ years building production-grade integration layers, semantic context gateways, or RAG endpoints consumed by LLMs and autonomous AI agents
• Proficiency in Advanced API Design & Context Optimization
• Production-level proficiency in one or more of: C# (.NET Core), Java, Python, or Node.js/TypeScript
• Proficiency in Enterprise Scalability & Traffic Management
• Proficiency in Lock & Contention Mitigation (API & Database Tier)
• Proficiency in Hardened Security, Governance & AI Isolation

Preferred Experience

• GraphQL and dynamic JSON/gRPC filtering layers (zero-waste data fetching)
• Custom MCP server development for LLM context exposure
• Heterogeneous schema merging for LLM tool-calling (e.g., relational DBs, analytics platforms like Pendo/Hotjar, observability tools)
• Semantic token-aware API pagination and streaming
• Context-aware gateways for conditional object graph hydration based on agent intent
• Edge performance: CloudFront Functions, Lambda@Edge, HTTP/3, WebSockets
• PostgreSQL and OpenSearch/Elasticsearch access layers with sub-millisecond caching
• Reactive streams and rate-limiting for Amazon MSK (Kafka), SQS, and HTTP endpoints
• Circuit Breakers, Bulkheads, and Retry-with-Exponential-Backoff (Polly, Resilience4j, or equivalent)
• Amazon MemoryDB / Redis OSS / Valkey for rate limiters, session caches, and semantic query caching
• Optimistic Concurrency Control (OCC) via eTags/versions; Pessimistic Locking only where strictly necessary
• CQRS separating high-volume writes from intensive read queries in PostgreSQL
• Asynchronous write delegation for high-contention API writes to Kafka/MSK
• Zero Trust security: OAuth2, OIDC, mTLS, and AWS Lake Formation
• Security proxy layers over Amazon Bedrock (prompt injection filtering, PII redaction, API token quota enforcement)
• End-to-end API runtime tracing with OpenTelemetry (oTel) and Datadog