Senior Platform Engineer

Company Cox Automotive - USA Job Family Group Engineering / Product Development Job Profile Sr Software Engineer Management Level Individual Contributor Flexible Work Option Hybrid - Ability to work remotely part of the week Travel % No Work Shift Day Compensation Compensation includes a base salary in the range of $101,500.00 - $169,100.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate’s knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program. Job Description Cox Automotive’s Engineering & Technology organization is building a centralized Enterprise AI Integration Platform — the governed infrastructure layer that allows every team in the organization to connect AI agents (Claude, Copilot Studio, Claude Code) to enterprise data sources in a secure, observable, and self-service way. This Senior Platform Engineer will own the technical implementation of that platform: the central AI gateway server, the on-demand connector provisioning engine, the identity-driven session layer, and the observability stack that gives the organization full visibility into every AI tool call made against production data.  This is one of a small number of roles at Cox Automotive working at the intersection of enterprise infrastructure engineering and Model Context Protocol (MCP) — the protocol rapidly becoming the standard interface between AI agents and enterprise systems. The work is novel, the surface area is broad, and the organizational impact is significant.  What You'll Do: Design, implement, and optimize the central AI Gateway MCP server — the single governed endpoint through which all AI client connections route, built on FastAPI + uvicorn for high-concurrency enterprise workloads  Build and maintain the Redis ElastiCache session layer that binds Microsoft Entra identity to role-resolved MCP tool sets, including token lifecycle management, sliding TTL extension, per-user quota enforcement, and distributed rate limiting  Implement the on-demand connector provisioning engine — a system that provisions compute containers with enterprise client drivers, establishes VPC-internal network paths, and retrieves credentials from AWS Secrets Manager automatically when a user’s AI agent declares intent to access a data source  Build enterprise system connectors as MCP tool sets: Oracle DB, SharePoint Graph API, Rally, ServiceNow, and a vendor connector approval pipeline with ECR container image scanning and an Aurora-backed connector registry  Implement comprehensive automated testing: unit, integration, load testing (1,000+ concurrent users), and chaos testing for connector fault tolerance  Build and maintain the full observability stack: structured logging, Prometheus metrics, Kinesis Firehose → OpenSearch indexing, and Grafana dashboards for per-user, per-tool, per-session audit trails  Design and implement CI/CD pipelines for all platform components via GitHub Actions, with automated container image builds, ECS task definition updates, and blue/green deployments  Own security controls: Entra OIDC token validation, PII masking on all tool responses, WAF rule management, Secrets Manager integration with autorotation, and OWASP-aligned secure API design  Maintain and extend the existing Snowflake MCP codebase that forms the foundation of the platform, including session management, RBAC, PII masking, configuration management, and secrets integration modules  Develop troubleshooting and diagnostic tools for production support  Create documentation, runbooks, and operational playbooks for platform support and maintenance  Who You Are: Minimum Requirements:  Bachelor’s degree in a related discipline and 4 years’ experience in a related field. The right candidate could also have a different combination, such as a master’s degree and 2 years’ experience; a Ph.D. and up to 1 year of experience; or 16 years’ experience in a related field Python development (4+ years) with advanced async/await patterns, FastAPI, multiprocessing, and production performance optimization  Model Context Protocol (MCP) — hands-on implementation experience with MCP servers, tool definitions, and client integration patterns; ability to read and extend the protocol specification independently  AWS platform depth: ECS Fargate task lifecycle management, ElastiCache Redis (TLS, clustering, eviction policies), Secrets Manager, Route 53, ALB (sticky sessions, TLS termination), ECR, Aurora Postgres, SSM Parameter Store, CloudWatch, Kinesis Firehose  Microsoft Entra ID / Azure AD integration: OIDC federation, group membership extraction via Graph API or JWT claims, RBAC pattern implementation  Database integration and optimization: Oracle, PostgreSQL, Snowflake, SQL Server — including connection pooling, query optimization, and schema introspection  Distributed systems patterns: circuit breakers, retry with exponential backoff, bulkhead isolation, Redis-backed distributed state, graceful degradation  Container platform: Docker multi-stage builds, ECS task definitions, non-root container security, health endpoint implementation  REST API security: JWT validation, rate limiting, input validation, PII detection and masking  Observability: structured JSON logging, Prometheus client instrumentation, distributed tracing concepts, CloudWatch Logs Insights  Version control and CI/CD (Git, GitHub Actions, automated testing pipelines)  Availability for rotational on-call duties outside of standard business hours may be required Preferred Experience  High-concurrency MCP server development with proven experience supporting enterprise-scale concurrent sessions  Snowflake advanced optimization: warehouse sizing, query profiling, result caching, role-based access patterns  Infrastructure-as-code wit