AI Platform Engineer

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

📋 Description

• Design, develop, implement, 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.

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

• Facilitate standardized authentication, model access, prompt and context management, structured outputs, tool usage, logging, error handling, and rate-limit management.

• Set up CI/CD pipelines, versioning, testing, release management, rollback, change control, and LLMOps/MLOps lifecycle practices.

• Develop automated AI evaluation and regression-testing frameworks.

• Support production operations, 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, logging, monitoring, auditing, vulnerability management, disaster recovery, and business continuity.

• Construct secure data ingestion, transformation, indexing, retrieval, and RAG pipelines.

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

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

• Collaborate with AI Architects, AI/ML Engineers, Data Engineers, Product Engineering, ServiceNow developers, consultants, and client technology teams.

• Offer technical guidance, contribute to playbooks and documentation, and participate in architecture reviews, demos, implementation planning, and customer workshops.

• Transform recurring client requirements into scalable platform features and accelerators.

⛳️ 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 expertise in CI/CD, Git-based workflows, automated testing, infrastructure as code, and production release processes.

• Familiarity 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 similar.

• 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.

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

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

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

• Familiarity 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-oriented environment.

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

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Opportunities for professional development and continuous learning.

• Flexible working hours and remote work options.

• Collaborative and inclusive work culture.