AI Platform Architect

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, deploy, and sustain scalable platform capabilities for enterprise AI, machine learning, LLM, RAG, and agentic AI applications.

• Create reusable reference architectures, infrastructure patterns, deployment templates, integration components, and engineering standards.

• Construct secure integrations with the Anthropic API, Claude models, enterprise data, APIs, workflow systems, and authorized tools.

• Establish practices for CI/CD, LLMOps, MLOps, versioning, testing, release management, rollback, monitoring, evaluation, and lifecycle management.

• Provide support for production AI services through incident response, troubleshooting, root-cause analysis, capacity planning, and service-level monitoring.

• Design and manage cloud infrastructure across AWS, Microsoft Azure, Google Cloud Platform, or client-approved environments.

• Implement infrastructure as code, containerized deployments, identity and access controls, security, privacy, logging, auditing, vulnerability management, disaster recovery, and business continuity.

• Develop secure data-ingestion, transformation, indexing, retrieval, RAG, vector-search, and enterprise data-integration pipelines.

• Implement responsible AI safeguards, observability, tracing, output validation, source attribution, approval gates, and human-in-the-loop workflows.

• Build integrations between AI platforms, ServiceNow, enterprise APIs, identity providers, workflow tools, collaboration platforms, and line-of-business systems.

• Provide technical guidance and collaborate with AI Architects, AI/ML Engineers, Data Engineers, Product Engineering, ServiceNow developers, consultants, and client technology teams.

• Contribute to playbooks, runbooks, reference architectures, technical documentation, reusable modules, demos, architecture reviews, and customer workshops.

• Productionize Claude-powered and other enterprise AI solutions for secure, scalable, observable, and governed use.

⛳️ Requirements

• Over 5 years of experience in platform engineering, cloud engineering, DevOps, software engineering, data engineering, systems integration, or similar technical roles.

• Hands-on experience in designing and deploying cloud-native applications and services on AWS, Microsoft Azure, and/or Google Cloud Platform.

• Strong background with CI/CD, Git-based workflows, automated testing, infrastructure as code, and production release processes.

• Experience with Docker, Kubernetes, serverless services, or similar cloud-native platforms.

• Proficiency in programming and scripting languages such as Python, JavaScript/TypeScript, Java, Go, Bash, or others.

• Experience in designing and consuming REST APIs, integrating enterprise applications, and implementing authentication and authorization patterns.

• Hands-on experience with LLM-powered applications, generative AI services, AI/ML platforms, RAG systems, AI workflow automation, or related technologies.

• Familiarity with prompt and context engineering, token management, embeddings, vector search, RAG, structured outputs, tool use/function calling, evaluations, and model monitoring.

• Experience with logging, metrics, tracing, alerting, and incident management.

• Strong understanding of cloud security, identity and access management, secrets management, network security, and secure software development practices.

• Experience with relational databases, NoSQL databases, data warehouses, object storage, search platforms, or vector databases.

• Ability to thrive in a fast-paced, collaborative, and customer-focused environment.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related technical field; equivalent relevant professional experience will also be accepted.

• Preferred qualifications include hands-on experience with Claude, Anthropic API, MCP, LLM frameworks, MLOps, vector databases, Kubernetes operations, ServiceNow, consulting, professional services, enterprise architecture, or client-facing technical delivery experience.

🏝️ Benefits

• A diverse and inclusive workplace.

• An equal opportunity workplace and affirmative action employer.

• Disability accommodations available upon request.

• Relevant certifications in cloud platforms, Kubernetes, DevOps, security, data engineering, ServiceNow, AI/ML, or Anthropic technologies are advantageous.