<p>We are looking for a skilled AI Software Engineer to join our team in Phoenix, Arizona. In this long-term contract role. We want a full-stack software engineer who ships at AI speed without giving up engineering judgment. You'll use AI coding agents as your main tool, and you'll be the person who knows when the agent is wrong.</p><p><br></p><p>Responsibilities:</p><p>· <strong>Build department workspaces end to end.</strong> Ticket hubs, queues, tiles and filters for Client Services, Legal, HR and Compliance (e.g. a ClickUp-style filter builder, a performance-review system, a legal case tracker).</p><p>· <strong>Work on regulated workflows.</strong> Credit-dispute (e-OSCAR ACDV) queues with locking, auto-submit and audit trails, where a bug means a compliance issue, not just a broken screen.</p><p>· <strong>Replace CollectOne, one department at a time.</strong> Read legacy SQL Server data, mirror it into Postgres, and rebuild the daily screens staff rely on.</p><p>· <strong>Write database migrations safely.</strong> Plan apply-before-merge order, row-level security, and one-transaction-per-page-load rules.</p><p>· <strong>Wire integrations.</strong> Microsoft Graph mailboxes into tickets, Amazon Connect call screens, AWS Bedrock AI features (reply suggestions, PDF invoice analysis), S3 uploads, Stripe and QuickBooks.</p><p>· <strong>Drive AI agents well.</strong> Write clear prompts and specs, break work into small stacked PRs, and review every line the agent writes.</p><p>· <strong>Keep CI honest.</strong> Respect the guard checks (page index, lint ratchet, migration hygiene, secret scanning) and add new guards when a mistake could repeat.</p><p>· <strong>Sit with users.</strong> Turn a messy request from a supervisor into a clear spec, then show them the working screen.</p>
<p><strong>Robert Half is working with a client who is looking to hire a Machine Learning Engineer</strong> to help operationalize machine learning models as part of a growing enterprise AI program.</p><p>This role will sit between Data Science and Engineering and will focus on taking models from experimentation into reliable, scalable production environments.</p><p>Responsibilities</p><ul><li>Develop and deploy machine learning models into production.</li><li>Build reusable ML pipelines for training, testing, deployment, and monitoring.</li><li>Partner with Data Scientists to productionize predictive models.</li><li>Develop APIs and services that expose machine learning capabilities to enterprise applications.</li><li>Monitor model performance, drift, and reliability.</li><li>Build automated testing and deployment processes for ML workloads.</li><li>Optimize model performance and infrastructure utilization.</li><li>Work with Data Engineering teams to establish reliable training and inference datasets.</li></ul><p><br></p>
<p>Our client is seeking a highly technical and innovative AI Solutions Engineer to design, build, and maintain internal applications, automations, and AI-powered tools that improve operational efficiency across the organization. This is not a traditional product development role. Instead, this individual will focus on solving business challenges through custom software development, workflow automation, system integrations, and practical applications of artificial intelligence.</p><p>The ideal candidate thrives in fast-paced environments, enjoys transforming ambiguous business needs into working solutions, and is comfortable partnering with both technical and non-technical stakeholders. This position offers the opportunity to work on a wide variety of projects while leveraging modern software development practices, cloud technologies, and AI capabilities to drive operational excellence.</p><p>Key Responsibilities</p><ul><li>Design, develop, and support internal applications, dashboards, automation tools, and workflow solutions that enhance business operations.</li><li>Build and integrate AI and Large Language Model (LLM) capabilities into existing processes, including document analysis, classification, workflow routing, content generation, summarization, and reporting.</li><li>Develop and maintain integrations between internal systems and third-party platforms using APIs and web services.</li><li>Rapidly prototype new solutions, gather business feedback, and evolve prototypes into scalable, maintainable production applications.</li><li>Collaborate with cross-functional teams to identify process improvement opportunities and implement technology-driven solutions.</li><li>Ensure applications meet security, privacy, governance, and compliance requirements.</li><li>Create and maintain technical documentation, architecture diagrams, and operational procedures to ensure ongoing supportability and audit readiness.</li><li>Monitor, troubleshoot, and enhance deployed solutions to ensure reliability and performance.</li></ul><p><br></p>