• Desenvolver e melhorar sistemas que aumentam a segurança dos dados. • Criar APIs e integrar sistemas que autenticam e protegem usuários. • Suportar outros times no uso seguro de IA, incluindo orientações e revisões. • Implementar testes automatizados para garantir qualidade dos sistemas. • Modernizar projetos de IA, mantendo-os seguros e eficientes. • Atuar em mudanças e criações de infraestrutura para suportar IA nos produtos. • Ajudar a implantar código de forma automatizada e segura (CI/CD).

Role Description We are seeking an Associate AI/ML Engineer (early‑career) who is excited to grow in a supportive, collaborative environment. You’ll be set up for success with clear expectations, opportunities to pair with senior engineers, and mentorship as you learn‑by‑doing—contributing to AI services, exploring Generative AI, and building foundational skills across machine learning and data engineering. We value curiosity, steady progress, and thoughtful questions as much as technical output. You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges. Primary Responsibilities: - AI/ML Solution Development - Implement and iterate on AI and machine learning solutions (including Generative AI) by building prototypes, integrating models into services, and improving quality based on evaluation results. - Model Training, Evaluation & Optimization - Support proof‑of‑concepts and model experiments and help baseline performance using clear evaluation metrics (with guidance on approach and tooling). - Platform & Infrastructure Engineering - Contribute to training and inference pipelines using Databricks, PySpark, and cloud platforms (AWS, Azure, GCP) with guidance from senior engineers. - Generative AI & Advanced Techniques - Learn and apply GenAI building blocks such as RAG and prompt orchestration tools (e.g., LangChain); exposure to vector databases is a plus. - Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI. - Support performance and cost improvements (e.g., caching, batching, basic optimization), and learn model optimization techniques (quantization/distillation) as needed. - Software Engineering & APIs - Contribute to building and testing APIs (e.g., REST with FastAPI) and learn delivery fundamentals such as containers (Docker) and simple app frameworks (e.g., Flask/Streamlit) as needed. - Collaboration & Communication - Collaborate with cross‑functional partners to understand business needs, ask clarifying questions, and communicate progress and results clearly. - Leadership, Mentorship & Culture - Participate in design and code reviews, learn from feedback, and contribute to team standards for quality, safety, and trust. Qualifications - Bachelor’s degree in Computer Science, IT, Data Science, or a related field. - 1+ years of software engineering experience (including internships, co‑ops, academic, or personal projects) delivering well‑tested applications and services. - 6+ months of AI/ML engineering experience, including prototyping, evaluation, and supporting deployment/monitoring in collaboration with senior engineers. - 6+ months of hands‑on experience (coursework, internships, or projects) with Python and SQL; familiarity with Java and scripting is a plus. - 6+ months of experience with any one major cloud platform (AWS, Azure, or GCP) through internships, labs, or projects or professional experience. Preferred Qualifications - Familiarity with MLOps concepts (experimentation tracking, model packaging, deployment patterns, and monitoring basics). - Exposure to Infrastructure as Code tools such as Terraform or CloudFormation (learning‑level or project experience). - Awareness of data governance and access control concepts; familiarity with Databricks features like Delta Lake and Unity Catalog is a plus. - Familiarity with common AI/ML libraries and basic patterns for integrating models into applications (inference, evaluation basics, and logging/monitoring fundamentals). - Exposure to big data technologies such as Spark; familiarity with ecosystem tools (e.g., Kafka/Hadoop) is a plus. - Basic understanding of data science fundamentals (statistics/probability, metrics, and data modeling); deeper coursework or hands‑on project experience is a plus. - Exposure to Databricks and Spark (PySpark/SparkSQL) through coursework, projects, or professional experience; familiarity with building basic data pipelines is a plus. - Familiarity with distributed data processing concepts (batch/streaming fundamentals, data partitioning, and performance basics). - Foundational understanding of clean, maintainable code, debugging, and basic API/service concepts; eager to learn system design and modern engineering best practices. - Ability to design, build, deploy, and operate production‑ready services with guidance, including exposure to CI/CD and cloud infrastructure. Benefits - Comprehensive benefits package. - Incentive and recognition programs. - Equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). Application Deadline This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.

• Evaluate AI-generated transport forecasts by assessing the accuracy and quality of forecasts and responses using a provided rubric

Role Description As the business invests in AI and automation as core operating infrastructure, they are hiring an AI Specialist to lead the function: evaluate the tools, design the workflows, train the people who will use them, and report on what actually moved the needle. This is a hands-on strategist-operator role. You will not be writing strategy decks in isolation. You will be embedded with department leaders across: - Estimating - Recruiting - Marketing - Project Management Within your first 90 days, success looks like: - 2–3 production AI workflows live in priority departments - Documented SOPs - Measurable time savings or accuracy gains - Active adoption by the team they were built for You will work alongside IT and security to ensure every solution clears compliance, data privacy, and risk review before it touches client data. Responsibilities - Ecosystem Evaluation & AI Implementation - Audit the current software stack to identify automation and AI-integration opportunities with the strongest ROI - Design and deploy AI solutions using leading platforms — Microsoft Copilot, OpenAI / ChatGPT Enterprise, Anthropic Claude, Sora, and domain-specific tools - Stay current with generative AI advancements and recommend what to adopt, defer, or ignore - Workflow Automation & Cross-Departmental Integration - Build API connections, scheduled triggers, and multi-step workflows that streamline operations across estimating, recruiting, marketing, project management, and back office - Develop reusable prompt systems and frameworks the company can scale without rebuilding from scratch each time - Document workflows for repeatable, auditable, transferable execution - Stakeholder Engagement & Training - Partner with department leaders to identify high-leverage use cases and translate technical concepts into practical business applications - Train teams on adopting new AI tools and workflows — and remain accountable for whether adoption sticks - Write SOPs, internal guides, and onboarding documentation that get used, not shelved - Prototyping, Testing & Optimization - Prototype AI-assisted systems and rigorously test for accuracy, scalability, and ROI before broader rollout - Iterate based on usage data and stakeholder feedback - Recommend what to scale, what to refactor, what to sunset - Compliance, Security & Risk - Work with IT and security teams to ensure every AI solution meets compliance, data privacy, and risk management standards - Establish guardrails around what data can and cannot be processed in which tools - Reporting & ROI Analysis - Prepare clear, executive-ready reports on implemented AI solutions and their measurable business impact - Surface what is working, what is not, and what needs leadership decisions to move forward Qualifications - 3+ years of experience in AI systems development, automation design, or data integration - Hands-on production experience with workflow automation tools — at least two of Power Automate, Zapier, or n8n — including multi-step flows with conditional logic and error handling - Strong fluency with generative AI models and prompt engineering (ChatGPT Enterprise, Microsoft Copilot, Claude, or equivalent) - Scripting ability in Python, JavaScript, or similar for cases that exceed no-code capability - Bachelor's degree in Computer Science, Engineering, Data Science, or a related field (Master's a plus) - Excellent problem-solving and stakeholder-engagement skills — comfortable presenting to and training department leaders - Working understanding of business operations in professional services, construction, or technical industries Nice to Have - Experience using AI inside the Microsoft 365 ecosystem (Copilot Studio, Power Platform, SharePoint, Teams) - Familiarity with construction management platforms such as Procore, Bluebeam, Autodesk Construction Cloud, or PlanGrid - Prior work in construction, AEC, engineering services, or other operations-heavy industries - Experience preparing ROI reports and dashboards for executive stakeholders Benefits - Full-time, long-term role with growth potential as the AI function matures - Compensation up to $10/hour USD - Direct ownership of the AI and automation function — not a junior support seat - Remote-first work environment with async-heavy collaboration How to Apply Submit your application through Workable and complete the required Aptive Index assessment here: https://assessment.aptiveindex.com/s/w3jwvu61boKX Applications without a completed Aptive assessment will not be reviewed. Data Privacy Notice By applying, you consent to being contacted via the contact information provided in your application for recruitment purposes only. Interview Scheduling Notice Initial screening calls are conducted in US Mountain Standard Time (MST), within a 3:00 AM – 1:00 PM MST window. We sincerely appreciate the flexibility our candidates show in accommodating the time difference, and we will make every effort to schedule a slot that works for you.