AI Platform Architect

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

📋 Description

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

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

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

• Set up and manage CI/CD pipelines, LLMOps/MLOps capabilities, evaluation frameworks, monitoring, and lifecycle management.

• Oversee cloud infrastructure, infrastructure-as-code, containers, Kubernetes, serverless services, identity, access, security, logging, and disaster recovery.

• Develop data ingestion, transformation, indexing, retrieval, and RAG pipelines.

• Implement responsible AI safeguards, observability, tracing, governance, auditability, and compliance controls.

• Create integrations among AI platforms, ServiceNow, enterprise APIs, identity providers, workflow tools, and line-of-business systems.

• Collaborate with AI Architects, engineers, data teams, ServiceNow teams, product engineering, and client stakeholders.

• Provide technical guidance, contribute to playbooks and documentation, and transform recurring client requirements into reusable platform features.

• Engage in technical discovery, architecture reviews, demos, implementation planning, and customer workshops.

• Support production operations, incident response, troubleshooting, root-cause analysis, capacity planning, and service-level monitoring.

⛳️ Requirements

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

• Practical experience with AWS, Microsoft Azure, and/or Google Cloud Platform.

• Strong background in 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 Python, JavaScript/TypeScript, Java, Go, Bash, or other comparable programming and scripting languages.

• Familiarity with designing and consuming REST APIs and implementing authentication and authorization patterns.

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

• Knowledge of 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.

• Comprehensive knowledge 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.

• Excellent problem-solving, troubleshooting, communication, and documentation skills.

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

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

🏝️ Benefits

• Diverse and inclusive workplace.

• Equal opportunity workplace and affirmative action employer.

• Disability accommodation support.