Role Description The AI Platform Engineer is responsible for designing, building, and operationalizing the organization's AI platform capabilities across cloud infrastructure, enterprise systems, and customer-facing digital platforms. This role serves as a technical leader within the IT organization and partners closely with Digital Development, Enterprise Systems, Operations, and business stakeholders to create scalable, secure, and reusable AI-enabled platform services that enhance both internal operations and external digital user experiences. A core function of this role is establishing and evolving the organization's AI Service Layer and supporting platform architecture including: - AI orchestration services - Reusable APIs - Customer-specific deployment models - Scalable cloud-native platform services This role bridges AI engineering, cloud architecture, SaaS platform engineering, DevOps collaboration, and enterprise data enablement to ensure AI capabilities can be consistently deployed, integrated, governed, and scaled across both enterprise operations and customer-facing digital platform experiences. Responsibilities - AI Platform Architecture & Engineering: - Design, develop, and maintain reusable AI platform services and infrastructure components that support enterprise AI initiatives and customer-facing digital platforms, including AI APIs, orchestration services, retrieval-augmented generation (RAG) pipelines, prompt management, vector search capabilities, model integration frameworks, and reusable backend AI services. - Digital Platform AI Enablement: - Design and implement AI capabilities that enhance customer-facing digital platforms and SaaS applications, including intelligent workflows, conversational interfaces, recommendation systems, predictive insights, automation services, and AI-assisted user experiences. - Partner closely with frontend, backend, and UX teams to ensure AI capabilities are seamlessly integrated into unified digital platform experiences. - AI Service Layer Development: - Build and maintain a centralized AI Service Layer that standardizes how enterprise systems, digital platforms, and SaaS applications consume AI capabilities, ensuring reusable patterns for model access, prompt orchestration, logging, security, governance, and scalable AI integration across customer-facing and internal solutions. - Enterprise Data & AI Enablement: - Partner closely with Data Integrations Engineering and Enterprise Systems teams to ensure enterprise data assets are accessible, structured, secure, normalized, and optimized for AI and analytics workloads across both internal and customer-facing systems. - SaaS Platform Architecture & Deployment Support: - Support scalable multi-tenant and customer-specific SaaS deployment models, including customer environment provisioning standards, AI service deployment architecture, database isolation strategies, deployment automation, and platform scalability best practices. - Technical Leadership & Cross-Functional Collaboration: - Collaborate closely with DevOps, Backend Engineering, Data Integrations, Enterprise Systems, Frontend Development, and UI/UX teams to define scalable AI integration standards, reusable AI-enabled development patterns, and AI platform best practices across the organization. - Partner with business departments including Operations, Sales, R&D, and other functional teams to identify opportunities for AI-enabled process improvement, intelligent automation, predictive insights, and enhanced digital platform capabilities that align with organizational objectives and operational needs. Qualifications - Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Engineering, or related field. - 5+ years of experience in AI engineering, machine learning engineering, AI platform development, or related technical roles. - Demonstrated experience building and deploying AI-enabled applications, AI services, or customer-facing AI capabilities in production environments. - Strong proficiency in Python, SQL, REST APIs, and AI service development. - Experience designing and deploying AI/ML services using Azure, Anthropic, vector databases, or related AI tooling. - Experience integrating AI capabilities into customer-facing web applications, SaaS products, or digital platform experiences. - Familiarity with scalable SaaS application architectures, API integration patterns, and AI orchestration workflows. - Familiarity with relational databases, secure data access concepts, and customer-aware data architectures. - Strong analytical, systems-thinking, and problem-solving capabilities. - Ability to clearly communicate technical concepts and AI solution designs to both technical and non-technical stakeholders. - Ability to work independently and collaboratively within cross-functional teams including Backend Engineering, Frontend Development, DevOps, Data Integrations, and UI/UX. - Willingness to travel occasionally (approximately 10%). Preferred - Master's degree in Computer Science, Artificial Intelligence, Data Engineering, or related field. - Experience building enterprise AI service layers, AI orchestration platforms, or reusable AI-enabled application services. - Experience integrating AI capabilities into customer-facing SaaS applications or digital platform experiences. - Experience with Azure AI Services, Azure Functions, Azure SQL, Azure Data Factory, Event Grid, Service Bus, or related Azure platform services. - Experience working within scalable SaaS application environments and customer-aware deployment models. - Experience with observability, monitoring, logging, and operational support for AI-enabled services. - Experience implementing secure AI governance, model access controls, and operational AI best practices. - Experience mentoring engineers or providing technical leadership across cross-functional development teams. - Relevant Azure, AI, or cloud-related certifications. Company Description USALCO is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law. As a general policy, USALCO does not offer employment visa sponsorships upon hire or in the future.

• Craft fault-tolerant data pipelines and distributed systems to support millions of students. • Effective communicator who collaborates well with distributed engineering, product, and design teams; experience explaining data architecture to both technical and non-technical audiences. • Ensure that timely, accurate data and metrics are delivered consistently. • Partner with your peer engineers and product owners on getting features and products to market. • Evolve data ownership and fluency across our teams, allowing us to bring new insights to customers easily and cost-effectively.

Role Description We’re looking for a Platform Engineering Intern to help build and support the core services that power Optura’s AI Platform. In this role, you’ll work alongside experienced engineers on systems that enable AI orchestration, routing, reliability, and observability in real-world healthcare environments. You’ll gain hands-on experience building production-ready software while contributing to a platform designed for scale, security, and operational excellence. Location: Open to remote or candidates located in the San Francisco Bay Area, Nashville Metro Area, or Raleigh, NC Area. What You’ll Do - Contribute to platform services in Python and TypeScript that support orchestration, routing, model gateways, retrieval-augmented generation (RAG), and evaluation workflows - Work with AI-assisted development tools (e.g., Claude, Cursor) alongside testing, linting, and benchmarking tools to improve engineering velocity and quality - Support the development, deployment, and monitoring of services with guidance from senior engineers - Help improve system reliability, observability, and performance through metrics, logging, dashboards, and debugging - Assist with building AI platform capabilities such as prompt management, evaluations, and integrations with multiple model providers - Work with data and storage systems including Postgres, caching layers, and vector search technologies - Learn and apply security and compliance best practices relevant to healthcare and HIPAA-aware systems Qualifications - Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field - Experience programming in Python, TypeScript, or similar modern languages through coursework, internships, research, or personal projects - Interest in AI systems, distributed systems, cloud infrastructure, or developer platforms - Familiarity with cloud platforms, containers, APIs, or databases is a plus - Strong problem-solving skills and eagerness to learn in a fast-paced startup environment - Excellent communication and collaboration skills Nice to Have - Exposure to AI/ML concepts such as LLMs, RAG, agents, or prompt engineering - Experience with Docker, Kubernetes, Terraform, or cloud services (AWS preferred) - Familiarity with observability tools, CI/CD pipelines, or backend infrastructure - Interest in healthcare technology or regulated environments Benefits - Work on cutting-edge AI infrastructure solving meaningful healthcare challenges - Gain mentorship from experienced startup and platform engineers - Contribute to production systems used in real-world healthcare environments - Flexible and collaborative remote-friendly culture - Opportunity to grow into future full-time engineering roles at Optura

Role Description You will be: - Shaping and evolving the AI platform architecture across cloud infrastructure and application services. - Leading platform deployment activities and infrastructure automation initiatives. - Owning and maintaining Kubernetes manifests, CI/CD pipelines, and container build images. - Driving system hardening, reliability, and production readiness improvements. - Making key architectural decisions connecting platform, infrastructure, and application layers. - Collaborating with engineering teams to support scalable and efficient platform operations. Qualifications - 5+ years of relevant experience. - Practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery. - Strong expertise in Terraform (preferred) or similar IaC tools, Helm, and GitOps (Argo CD/Flux a plus). - Experience with CI/CD (e.g., GitHub Actions). - Deep knowledge of production Kubernetes (deployments, services, HPA, RBAC, etc.). - Experience with multi-orchestrator environments (Kubernetes + AWS ECS, GCP Cloud Run, Azure, etc.). - Solid understanding of data management and Python development. - Familiarity with observability tools (e.g., OpenTelemetry, Prometheus, Grafana). - Work from the European Union region and a work permit are required. Requirements - Nice to have experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work. - Interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches. Recruitment Process - CV review - HR call - Technical Interview - Client Interview - Decision