• Design, build, and deploy generative AI applications using Google Gemini (Pro, Ultra, Flash), PaLM 2, and other Google-hosted foundation models via Vertex AI. • Implement Retrieval-Augmented Generation (RAG) architectures using Vertex AI Search, Vector Search, and document embedding pipelines for enterprise knowledge retrieval. • Develop multi-modal AI capabilities leveraging Gemini's vision, text, and code understanding for hospitality use cases such as guest experience, analytics, and operations. • Build and maintain agentic AI workflows and orchestration using LangChain, LlamaIndex, or Google Agent Builder — integrating tools, APIs, and enterprise data sources. • Optimize prompt engineering strategies, system instructions, and grounding mechanisms for production-grade LLM deployments. • Develop end-to-end ML pipelines from data ingestion and feature engineering through model training, evaluation, and production deployment on Vertex AI Pipelines / Kubeflow. • Apply advanced data science techniques — statistical modelling, time-series forecasting, recommendation systems, and anomaly detection — for hospitality and gaming analytics. • Build scalable data transformation and feature engineering workflows using BigQuery, Dataflow, and Pub/Sub. • Implement model monitoring, drift detection, and automated retraining strategies to ensure sustained model performance in production. • Leverage TensorFlow, JAX, or PyTorch for custom model development where pre-trained solutions are insufficient. • Architect and manage cloud-native AI infrastructure on GCP — including Vertex AI, BigQuery ML, Cloud Run, GKE, Cloud Functions, and Cloud Storage. • Design secure, scalable, and cost-optimized GCP environments aligned with enterprise compliance requirements and CLIENT's data governance standards. • Implement CI/CD pipelines for ML model serving using Cloud Build, Artifact Registry, and Vertex AI Model Registry. • Set up monitoring, observability, and alerting for AI/ML workloads using Cloud Monitoring, Cloud Logging, and custom dashboards in Looker. • Build agents with Google ADK, deploy with Cloud Run / Agent Engine with Vertex. • Design and implement conversational AI agents using Dialogflow CX and Agent Builder for guest-facing and internal automation use cases. • Partner with CLIENT's business and technology stakeholders to define AI use cases, prioritize the roadmap, and translate requirements into technical deliverables. • Champion responsible AI practices — model fairness, explainability, content safety, and data privacy — across all AI solution designs. • Produce and maintain technical documentation including architecture decision records (ADRs), API specs, model cards, and runbooks. • Mentor junior engineers and lead knowledge-sharing sessions; contribute to AI community of practice within the delivery organization.

We are looking for an Applied AI Engineer to help us make Foley truly AI-native — not by layering tools on top, but by rethinking how work gets done across the company. You’ll operate as a forward-deployed builder, embedded with business teams to identify high-leverage problems and ship real solutions. This is a hands-on role where you’ll design, build, and deploy AI-powered systems that improve how we operate, make decisions, and deliver value. This is not a research role. You build, you ship, and you measure impact. What You’ll Do Build & Ship Solutions - Design and build AI-powered systems end-to-end, including agentic workflows, internal tools, automation pipelines, and business applications - Own your work from concept through production, including iteration and improvement - Use AI-assisted development and modern tooling to move quickly without sacrificing quality Embed with the Business - Work directly with operations, compliance, sales, and product teams to understand real workflows and pain points - Translate ambiguous, messy processes into clear, scalable systems - Operate as part of cross-functional “tiger teams” focused on high-impact problems Drive Outcomes, Not Just Output - Define success metrics and measure whether your solutions improve speed, quality, or decision-making - Close the loop by evaluating what worked, what didn’t, and what to improve Build for Scale & Reuse - Design composable solutions that integrate into the broader platform - Think in reusable capabilities, not one-off scripts Operate with Judgment & Guardrails - Build with awareness of regulatory constraints (DOT, FMCSA, PII) - Apply strong judgment when using AI to ensure quality, trust, and compliance Contribute to the Builder Community - Share patterns, tools, and learnings with other engineers and teams - Review work and help raise the bar for how we build Who You Are We’re looking for builders who think in systems and care about outcomes. You may come from different paths, but you share a common trait: you build things that work. You might come from: - Data Science → GenAI Builder: You moved from analysis to building production systems - Business-Facing Engineer: You bridge technical execution and business context - Domain Expert Turned Builder: You started in a business function and taught yourself to build solutions Must-haves - You have built and shipped real products, tools, or systems (portfolio, GitHub, or equivalent) - You are fluent in Python, including APIs, data handling, and deployment patterns - You have hands-on experience building with LLMs (e.g., prompting, tool use, RAG, agents) - You think in systems and can map business workflows to technical solutions - You communicate clearly with both technical and non-technical stakeholders Strong Signals - You’ve built and deployed multi-step or tool-using AI systems - You’ve worked with orchestration frameworks (e.g., LangGraph, CrewAI, MCP) - You’ve built solutions involving document processing, structured extraction, or voice - You’ve implemented observability for AI systems (e.g., Langfuse, LangSmith) - You understand knowledge graphs or entity resolution - You’ve worked in regulated environments (transportation, finance, healthcare, compliance) - You’ve independently taken a process from “this is broken” to a shipped solution Not Required - A specific degree or traditional background - Experience at large tech companies - ML research or publications - Deep infrastructure or DevOps specialization Location: This role is primarily remote (US based), with the expectation of occasional visits to our offices for team collaboration, training, or company events. This role may be based remotely out of the following states: Arizona, California, Colorado, Connecticut, Florida, Georgia, Illinois, Indiana, Kansas, Maryland, Massachusetts, Michigan, Nebraska, New Hampshire, New Jersey, New York, North Carolina, Pennsylvania, South Carolina, Tennessee, Texas, Virginia, Wisconsin. About us At Foley, we’re reimagining how safety-sensitive industries hire, stay compliant, and manage risk. We’ve evolved into a modern SaaS company with an all-in-one, AI-ready platform that helps transportation, construction, distribution, and utility businesses operate faster, smarter, and safer. As we continue to grow, we’re looking for curious, strategic thinkers who thrive in complexity, are motivated by making an impact, and want to join a team that’s passionate about building great products and supporting customers. Our core values — Teammateship, Grit, and Innovation — guide everything we do. Whether we’re collaborating internally or helping customers, we approach every challenge with optimism, humor, and a shared commitment to success. Benefits Foley offers a comprehensive benefits package that includes medical, dental, and vision coverage, a 401(k) with company match, paid time off and holidays, wellness programs, and an employee assistance program. Equal Employment Opportunity Foley is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, protected veteran status, or any other legally protected characteristic. Reasonable Accommodations If you require a reasonable accommodation during the application or interview process, please contact us at careers@foley.io Employment Status Employment with Foley is on an at-will basis. Nothing in this job posting or in future communications should be construed as a contract of employment. Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

SRS Distribution, a wholly owned subsidiary of The Home Depot, currently operates under a family of distinct local brands encompassing more than 760 locations across 47 states. For more information, visit www.srsdistribution.com. Where you’ll work: - Must preferably reside in one of the following states: Oregon, Washington, California: Up to 75% travel. What you’ll do: SRS Distribution Inc. has an opportunity for a Training Program Instructor to join our fast-paced, dynamic company. You will lead a best-in-class internal CDL & Crane Training school in a classroom environment. The instructor will deliver CDL Driver and NCCCO training to SRS’ associates wanting to become CDL Drivers and Crane Operators. Responsibilities include delivery of standardized curriculum to prepare associates for the CDL exam by conducting classroom-based study, as well as training on vehicle operation, equipment management and overall safety. As a liaison and partner with Branch Management, you are the key point of contact regarding training and trainee performance. - Deliver instructional activities to include classroom learning (traditional and virtual) and on-the-job training that facilitates active learning experiences that include field course training. - Independently manage all pre-training prep work, learning schedules and calendars, maintain participant records (e.g., test scores, evaluations, and attendance), as well as required Workday Learning Administration requirements. - Comply with all Company standards and policies, applicable health and safety rules and regulations, as well as applicable local, state, and federal laws. - Build strong and trusting relationships with team members, business partners, and students; work collaboratively and cross-functionally to achieve objectives; and communicate with energy and positivity to motivate, influence, and inspire commitment and action. - Build relationships with internal and external business partners for program development and project execution. Develop and maintain an extensive network of relationships with current and potential customers in the transportation industry, including government clients, original equipment manufacturers, suppliers, universities, and technology firms. - Provide overall project support, including managing project summary and progress reports, contracts, and participating in project team meetings. - Manage projects, execute technical tasks, take responsibility for overall training schedule, budget, quality, and client satisfaction, serving as the primary interface to the student. What we look for: - Bilingual in Spanish is preferred. - Formal training or education in adult learning, human performance technology, training delivery, and student evaluation are highly desirable. - Must possess a valid CDL License and Medical Card. - Must possess a current NCCCO Articulating Boom Crane (ABC) and Articulating Boom Loader (ABL) certification. - A high school diploma or GED. - Proficient in Microsoft Office Suite (PowerPoint, Excel, Word), basic OS tools, and LMS applications. - Excellent presentations skills. Comfortable in the presentation of materials to large groups of people. - Time management and organizational skills should be exceptional, as well as an ability to assess and manage priorities. - Traveling up to 75% of the time. - Thrive in a fast-paced, rapidly changing environment. Not the right job for you? Register your details at the 'Introduce Yourself' link (top right) and we'll be in touch! Job Location: SRS Distribution - McKinney 7440 State Highway 121 McKinney, TX 75070-3104‎ As an Equal Employment Opportunity (EEO) employer SRS Distribution Inc., including all its subsidiaries, provides job opportunities to qualified individuals without regard to actual or perceived race, color, creed, religion, national origin, sex, gender, age, disability, gender identity, sexual orientation, citizenship status, uniform service, veteran status, marital status, genetic information, physical or mental disability, or any other characteristic in accordance with applicable federal, state, and local EEO laws. If you are an individual with a disability or a disabled veteran and require a reasonable accommodation in applying for any posted position, please contact Human Resources at US: 855.556.3221, or by email to: HR@Help.SRSDistribution.com with the nature of your accommodation request and include the Business name, location and title of the job opening. Please allow one (1) business day for a reply. All employment offers are contingent upon successful completion of a background check and drug screen, as permitted by law.‎ Competitive weekly/bi-weekly pay, discretionary bonuses, 401(k) with company match, Employee Stock Purchase Plan, paid time off (vacation, sick, volunteer, holidays, birthday, floating), medical/dental/vision, flexible spending accounts, company-paid life and short-term disability, plus optional long-term disability, and additional life insurance.‎

• Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. • Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. • Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements. • Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. • Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn’t done. • Lead Solutions Enablement Sprints: transfer AI deployment patterns to solutions consultants and partners with training materials and certification criteria. • Drive the intelligence loop: author strategic memos, present field findings weekly, contribute Agent Bricks and Skills, file RFCs for platform improvements. • Mentor junior FDEs on customer engagements, code reviews, and Deployment Kit quality.