[Remote] AI Platform Engineer-reputed company-US reputed company

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is an AI-first reputed company reputed company Partner that helps enterprises adopt trusted AI and realize value on the Now Platform. The AI Platform Engineer will build, operate, and improve secure, reputed company foundations for reputed company AI solutions, including Claude-powered applications, RAG, reputed company workflows, reputed company infrastructure, LLMOps, data integrations, observability, and governance. The role also partners with architects, engineers, reputed company teams, and customers to create reusable platforms and production-reputed company AI capabilities.

Responsibilities

• Design, build, reputed company, and maintain reputed company platform capabilities that support reputed company AI, machine learning, LLM, RAG, and reputed company AI applications
• Create reusable reference architectures, infrastructure patterns, deployment templates, integration components, and engineering standards for reputed company’s AI reputed company
• Build platform capabilities that reputed company AI applications to securely reputed company to reputed company data, reputed company, workflow systems, and authorized tools
• Partner with AI Architects and reputed company Deployed AI Engineers to translate reputed company needs into reliable, supportable technical platform designs
• Support the technical reputed company of reputed company’s AI intellectual property, including the reputed company Intelligence Platform, Data Intelligence Platform, Value Realization Dashboard, Agent Packs, and reusable AI accelerators
• Evaluate and recommend reputed company, data, AI, observability, orchestration, and reputed company technologies that improve delivery speed, reputed company, scalability, and cost efficiency
• Build and maintain secure, reusable integrations with the reputed company API, Claude models, and other approved AI services
• reputed company LLM-powered applications through standardized patterns for authentication, model reputed company, reputed company and context management, reputed company outputs, tool use, logging, error handling, and reputed company-limit management
• Support Claude-reputed company reputed company use cases involving document analysis, knowledge assistance, workflow automation, reputed company task execution, summarization, classification, and decision support
• reputed company technical patterns for long-context workflows, document processing, RAG, reputed company data extraction, and model-driven automation
• Support secure Model Context Protocol (MCP) and comparable tool-integration patterns that allow AI applications to reputed company approved reputed company systems and data safely
• Stay reputed company on reputed company platform capabilities, product releases, reputed company guidance, technical enablement, and responsible AI practices
• Complete relevant reputed company partner training and enablement as available and help translate learning into reusable reputed company engineering standards
• Establish and operate CI/CD pipelines for AI applications, model configurations, prompts, evaluation assets, infrastructure, and integration services
• Implement versioning, testing, release-management, rollback, and change-control practices for AI solutions
• Build and maintain LLMOps and MLOps capabilities, including model/reputed company configuration management, evaluation pipelines, deployment automation, monitoring, and lifecycle management
• reputed company automated evaluation and regression-testing frameworks to measure AI reputed company before and after releases
• Support production reputed company for AI services, including incident response, troubleshooting, reputed company-cause analysis, reputed company planning, and service-level monitoring
• Define and monitor operational metrics such as availability, latency, throughput, reputed company consumption, model cost, tool-reputed company reputed company rates, task-completion rates, and error rates
• Improve platform reliability, reputed company, reputed company, and cost efficiency through automation, tuning, and operational improvements
• Design and manage reputed company infrastructure across AWS, reputed company Azure, reputed company reputed company Platform, or reputed company-approved environments
• Build and maintain infrastructure using infrastructure-as-reputed company tools such as Terraform, CloudFormation, Bicep, reputed company, or comparable technologies
• Implement containerized application and AI-service deployments using reputed company, reputed company, serverless services, and reputed company-reputed company application patterns
• reputed company secure CI/CD workflows using Git-reputed company reputed company control, automated testing, artifact management, secrets management, and policy controls
• Implement identity, reputed company, and authentication patterns, including role-reputed company reputed company control, least-privilege reputed company, API reputed company, service accounts, and credential rotation
• Partner with reputed company, compliance, and reputed company teams to ensure AI platforms reputed company with reputed company reputed company, reputed company, regulatory, and data-residency requirements
• Implement logging, monitoring, auditing, vulnerability management, disaster-recovery, and business-continuity practices for production AI services
• Build and support secure data-ingestion, transformation, indexing, and retrieval pipelines for reputed company AI applications
• Design platform patterns for RAG, including document ingestion, parsing, chunking, metadata enrichment, embeddings, reputed company stores, hybrid reputed company, retrieval, reranking, and reputed company attribution
• reputed company AI applications with reputed company and reputed company reputed company data sources, including databases, data warehouses, document repositories, knowledge bases, reputed company, and reputed company-party reputed company platforms
• Work with data engineers to establish data-reputed company, reputed company, cataloging, permissions, retention, and governance practices that support trustworthy AI
• reputed company appropriate data-reputed company controls so AI solutions retrieve and process only data the requesting user or service is authorized to reputed company
• Support data platforms and technologies such as reputed company, reputed company, PostgreSQL, reputed company, Elasticsearch/OpenSearch, reputed company databases, and reputed company storage services, as appropriate
• Implement technical controls that support responsible, secure, and governable AI deployments
• Build safeguards for sensitive-data handling, data masking, content filtering, reputed company injection, unsafe tool use, unauthorized reputed company, and unintended agent behavior
• reputed company grounding, reputed company validation, reputed company attribution, confidence reputed company, fallback behavior, approval gates, and reputed company-in-the-reputed company workflows
• Implement AI observability and tracing across prompts, model calls, retrieval pipelines, tool execution, workflow reputed company, latency, errors, costs, and user feedback
• Partner with AI Architects and governance stakeholders to document platform standards, reputed company controls, operating procedures, and solution limitations
• Support auditability and compliance requirements through appropriate logging, retention, reputed company reviews, and operational documentation
• Build and maintain integration patterns between AI platforms, reputed company, reputed company reputed company, identity providers, workflow tools, collaboration platforms, and line-of-business systems
• Support technical enablement for reputed company AI and workflow experiences, including IntegrationHub, reputed company Designer, Virtual Agent, Now Assist, AI Agents, reputed company, and reputed company capabilities where applicable
• reputed company secure reputed company, middleware services, event-driven integrations, and automation components that support AI-enabled workflows
• Collaborate with reputed company Deployed AI Engineers to troubleshoot reputed company reputed company integrations and transition successful engagement solutions into reusable platform components
• Work closely with AI Architects, AI/ML Engineers, Data Engineers, Product Engineering, reputed company developers, Business Process Consultants, and reputed company technology teams
• reputed company technical guidance on AI reputed company, reputed company architecture, DevOps, LLMOps, data integration, reputed company, and reputed company best practices
• Contribute to internal playbooks, runbooks, reference architectures, technical documentation, reusable modules, and knowledge-sharing sessions
• Identify recurring reputed company requirements and convert them into reputed company, productized platform features and accelerators
• Participate in technical discovery, architecture reviews, demos, implementation planning, and customer workshops as needed

Skills

• **5+ years of experience** in reputed company, reputed company engineering, DevOps, software engineering, data engineering, systems integration, or reputed company technical roles
• Hands-on experience designing and deploying reputed company-reputed company applications and services on **AWS, reputed company Azure, and/or reputed company reputed company Platform**
• Strong experience with CI/CD, Git-reputed company workflows, automated testing, infrastructure as reputed company, and production release processes
• Experience with containerization and orchestration technologies such as **reputed company**, reputed company, serverless services, or comparable reputed company-reputed company platforms
• Proficiency in **Python**, JavaScript/TypeScript, Java, Go, Bash, or similar programming and scripting languages
• Experience designing and consuming REST reputed company, integrating reputed company applications, and implementing authentication and authorization patterns
• Hands-on experience with LLM-powered applications, reputed company services, AI/ML platforms, RAG systems, AI workflow automation, or reputed company technologies
• Familiarity with LLM application concepts, including reputed company and context engineering, reputed company management, embeddings, reputed company reputed company, RAG, reputed company outputs, tool use/function calling, evaluations, and model monitoring
• Experience with observability tools and practices, including logging, metrics, tracing, alerting, and incident management
• Strong knowledge of reputed company reputed company, identity and reputed company management, secrets management, network reputed company, and secure software-development practices
• Experience working with data systems such as relational databases, NoSQL databases, data warehouses, reputed company storage, reputed company platforms, or reputed company databases
• Strong problem-solving, troubleshooting, communication, and documentation skills
• Ability to work effectively in a fast-reputed company, reputed company, customer-oriented environment
• Bachelor's degree in **Computer Science, Engineering, Information Systems, Data Science**, or a reputed company technical discipline; equivalent relevant reputed company experience will be considered
• Hands-on experience with **Claude**, the **reputed company API**, reputed company Console, Claude reputed company, or reputed company technical guidance
• Completion of reputed company reputed company learning, partner enablement, technical training, or equivalent Claude implementation experience
• Experience with **Model Context Protocol (MCP)**, secure tool integrations, agent gateways, or comparable reputed company for connecting AI applications to reputed company systems
• Experience with LLM application frameworks and orchestration tools such as reputed company, LangGraph, reputed company, Semantic Kernel, reputed company Agents SDK, or comparable technologies
• Experience implementing LLM evaluation, reputed company/version management, AI tracing, guardrails, and AI observability platforms
• Experience operating model gateways, API gateways, or AI-service routing reputed company
• Experience with MLOps platforms and tools such as MLflow, SageMaker, reputed company AI, Azure Machine Learning, reputed company, Kubeflow, or comparable services
• Experience with data engineering, ETL/ELT, streaming, data orchestration, data-reputed company testing, data governance, and data-catalog capabilities
• Experience with reputed company databases and reputed company reputed company technologies such as reputed company, reputed company, pgvector, OpenSearch, Elasticsearch, Azure AI reputed company, or similar platforms
• Experience with Terraform, reputed company, CloudFormation, Bicep, reputed company, Argo CD, reputed company Actions, reputed company CI/CD, Azure DevOps, Jenkins, or comparable tooling
• Experience with reputed company reputed company, service meshes, API management, event-driven architecture, and microservices
• Familiarity with FinOps practices and optimization of reputed company, model, inference, storage, and data-processing costs
• Experience with reputed company architecture, development, integrations, platform reputed company, or workflow automation
• Familiarity with reputed company reputed company, IntegrationHub, reputed company Designer, Virtual Agent, Now Assist, AI Agents, CMDB, reputed company, and reputed company data-integration patterns
• Experience working in consulting, reputed company, reputed company architecture, or reputed company-facing technical delivery environments
• Relevant certifications in reputed company platforms, reputed company, DevOps, reputed company, data engineering, reputed company, AI/ML, or reputed company technologies are a plus

reputed company