Job Summary:
Seeking an AI Engineer with strong backend engineering expertise and experience building reliable data and AI services. The role will focus on backend/runtime services, APIs, session and identity context, enterprise integrations, and reliable delivery of data and AI responses. The engineer will work across Python, REST and streaming APIs, BigQuery, GCP, GKE, Kubernetes, Terraform, conversational AI, agent integrations, and knowledge graph interfaces while ensuring secure, observable, testable, and production-ready solutions. The role also includes technical leadership responsibilities such as owning backend design, conducting code reviews, mentoring engineers, and driving production readiness.

Key Responsibilities:
• Own backend design and service boundaries while remaining hands-on with implementation and delivery.
• Develop and maintain backend services using advanced Python, REST and streaming APIs, and asynchronous processing.
• Implement session and workflow-state management, retries, timeouts, caching, schema validation, and structured error handling.
• Design API-first integrations using Apigee, authentication and authorization, user-context propagation, versioned contracts, and rate limiting.
• Integrate backend services with UI applications, AI gateways, agents, BigQuery, and Stardog.
• Develop advanced SQL solutions using BigQuery, including curated and authorized views, query optimization, result transformation, pagination, filtering, masking, and role-aware data delivery.
• Integrate conversational AI and agent-based capabilities, including structured response payloads, citations, and graceful handling of unavailable downstream services.
• Integrate backend services with semantic and graph interfaces.
• Develop and manage cloud-native solutions using GCP, GKE, Docker, Kubernetes, and Terraform.
• Implement and manage service accounts, secrets, workload identity, networking, DNS, load balancing, and private connectivity.
• Develop automated build, test, deployment, promotion, rollback, credential rotation, and environment management processes.
• Implement unit, integration, contract, regression, performance, load, and resilience testing with automated quality gates.
• Establish logging, metrics, distributed tracing, dashboards, alerting, SLIs, and operational monitoring.
• Participate in incident response, root-cause analysis, recovery activities, and development of support runbooks.
• Apply secure coding, least-privilege access, identity propagation, secrets management, data masking, audit logging, and sensitive data protection practices.
• Conduct technical and code reviews, mentor engineers, manage technical dependencies, and drive production readiness.

Required Qualifications:
• Advanced Python development experience with strong backend engineering capabilities.
• Strong experience with REST and streaming APIs, asynchronous processing, session management, workflow-state management, retries, timeouts, caching, schema validation, and structured error handling.
• Strong experience with API-first design, authentication and authorization, user-context propagation, versioned contracts, and rate limiting.
• Hands-on experience with Apigee and enterprise API integrations.
• Advanced SQL experience and strong hands-on experience with BigQuery.
• Experience with curated and authorized views, query optimization, data transformation, pagination, filtering, masking, and role-aware data delivery.
• Working knowledge of conversational AI, agent integration, structured response payloads, citations, and AI service integrations.
• Experience integrating backend services with semantic and graph interfaces.
• Hands-on experience with GCP, GKE, Docker, Kubernetes, and Terraform.
• Experience with service accounts, secrets, workload identity, networking, DNS, load balancing, and private connectivity.
• Experience implementing CI/CD processes covering automated builds, testing, deployments, promotions, rollbacks, credential rotation, and environment management.
• Experience with unit, integration, contract, regression, performance, load, and resilience testing.
• Experience with observability practices including logging, metrics, distributed tracing, dashboards, alerting, and SLIs.
• Strong understanding of secure coding, least privilege, identity propagation, secrets management, masking, audit logging, and sensitive data protection.
• Strong troubleshooting and problem-solving skills, including incident response, root-cause analysis, recovery, and production support.
• Ability to conduct design and code reviews, mentor engineers, manage dependencies, and drive production readiness.