• Define and champion the overall AI strategy and roadmap in alignment with the company's product vision and business goals. • Lead the selection and integration of advanced machine learning models, algorithms, and deep learning techniques relevant to embodied AI (e.g., perception, manipulation, natural language understanding). • Foster a culture of innovation, rigorous research, and responsible AI development that supports the team's ongoing success. • Ensure that all AI systems adhere to the highest standards of safety, privacy, and ethical guidelines. • Partner with Hardware and Robot Software leadership to ensure the sensor suite and embedded compute are optimized for current and future AI model architectures. • Oversee the design, development, and deployment of on-robot and cloud-based AI systems, leveraging the existing team's expertise. • Establish MLOps best practices for efficient model training, deployment, monitoring, and iteration. • Drive research into novel AI solutions for complex robotics challenges, such as real-time planning, human-robot interaction, and adaptive motor control. • Deliver production-ready AI models that meet performance, latency, and reliability requirements for commercial deployment. • Spearhead the Sim2Real strategy, utilizing physics-based simulation (e.g., MuJoCo, Isaac Sim) to train robust policies that transfer seamlessly to hardware. • Accelerate our data flywheel strategy to combine teleoperation, synthetic data, and fleet learning to expand the fleet performance and reliability. • Champion the existing team's talent and represent their needs to senior leadership. • Develop a comprehensive hiring plan to staff and scale the AI team, including defining required roles (e.g., ML Engineers, Data Scientists, AI Researchers). • Lead recruitment, mentorship, and career development for all members of the AI team. • Manage the budget allocated for team salaries, equipment, and necessary infrastructure. • Forecast and manage the budget for cloud computing resources (GPUs, TPUs) necessary for large-scale model training and experimentation. • Secure and allocate funding for specialized datasets and data annotation services. • Evaluate and procure necessary software licenses and tools for AI development and simulation. • Regularly report on expenditure and resource utilization to senior leadership.

• Define and execute Mark43’s enterprise data and AI strategy, aligning technical foundations with business and product priorities • Lead the evolution of a scalable, trustworthy data platform that consolidates disparate data sources into a single source of truth • Establish standards for data governance, quality, observability, and responsible AI use in a regulated public-sector environment • Partner with Product, Sales, Operations, and People teams to identify high-value AI opportunities and rapidly prototype solutions • Guide the design and deployment of AI-powered workflows, analytics, and decision-support systems—not just dashboards • Collaborate with Engineering to embed intelligence into internal tools and future product capabilities • Translate complex data and model outputs into clear, actionable insights for executive and senior leaders • Personally lead deep-dive analyses on revenue performance, operational efficiency, customer outcomes, or organizational health • Build real-time, decision-oriented dashboards and metrics that drive accountability and results • Act as a trusted advisor to senior leadership on data, AI, and emerging technology trends • Align cross-functional stakeholders around shared metrics, priorities, and data-driven decision-making • Mentor and grow data and analytics talent as the function scales

AI Operations Engineer Concurrent Technologies Corporation Johnstown, PA Minimum Clearance Required: None Clearance Level Must Be Able to Obtain: Secret Employee Background Check Required Concurrent Technologies Corporation (CTC) is embarking on a strategic initiative to integrate Artificial Intelligence (AI) across our business. We are seeking a skilled and creative AI Application Integrator to implement innovative solutions by leveraging state-of-the-art AI models, APIs, and platforms. This role focuses on seamlessly integrating AI capabilities into existing systems and workflows to deliver practical, business-driven outcomes. This role is pivotal to our strategy of rapidly developing and deploying AI-powered applications that enhance our internal operations and solve complex national security challenges for our clients. The ideal candidate is a hands-on developer who excels at integrating various systems and consuming APIs from leading AI services (e.g., Azure OpenAI, Ask Sage). You will be responsible for building the connective tissue between powerful LLMs and our proprietary data and systems, creating tangible value and new capabilities for the organization. Key Responsibilities: - Design, develop, and deploy scalable machine learning models and AI algorithms. - Build and manage robust MLOps and GenAIOps pipelines to automate model training, testing, and deployment. - Collaborate with data scientists and software engineers to integrate AI models into our core products and services. - Implement data ingestion and transformation infrastructure to ensure high-quality data for model training. - Conduct model evaluation, performance monitoring, and debugging to ensure reliability and address issues. - Design and develop AI-powered applications by integrating third-party and internal AI services, including LLMs, via API calls. - Build solutions using modern AI development frameworks (e.g., LangChain, LlamaIndex) to orchestrate complex workflows, manage prompts, and connect models to diverse data sources. - Implement Retrieval-Augmented Generation (RAG) patterns by connecting LLMs to vector databases (e.g., Pinecone, ChromaDB) and other data stores to create context-aware, factual applications. - Collaborate with cross-functional teams to embed AI capabilities into new and existing software applications, ensuring seamless user experiences. - Work within our multi-cloud infrastructure, leveraging DevSecOps principles and Infrastructure as Code (IaC) to build, test, and deploy AI applications securely and efficiently. - Ensure all data handling and API interactions adhere to strict security and compliance protocols, particularly when dealing with sensitive government data. - Support the enhancement and integration of internal AI tools, like our Ask Sage chatbot, to drive operational efficiency across the company. Basic Qualifications: - Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related quantitative field plus a minimum of 4 years experience. - Proven experience as an AI, Machine Learning, or Software Engineer, with a minimum of [e.g., 3+] years of hands-on experience putting models into production. - Proficiency in programming languages such as Python (essential) and experience with relevant AI/ML frameworks like TensorFlow, PyTorch, or scikit-learn. - Solid understanding of mathematical and statistical concepts, including probability, linear algebra, and calculus. - Experience with cloud platforms (e.g., AWS, GCP, or Azure) for model deployment and scaling. - Strong proficiency in Python and extensive experience with consuming RESTful APIs. - Demonstrated experience building applications that integrate with third-party API-based services. - Experience building, optimizing, and maintaining Large Language Models and their application development lifecycle. - Experience with cloud platforms (AWS, Azure) and orchestration/containerization technologies (Docker, Kubernetes, Prefect, Ansible, etc.). - Strong problem-solving skills and the ability to work effectively in a collaborative team environment. Preferred Qualifications: - Direct experience building applications with AI orchestration frameworks such as LangChain or LlamaIndex. - Experience with .NET C# for backend development. - Experience with UI frameworks such as React and .NET Blazor. - Experience with graph databases such as Neo4j. - Experience with vector databases like Pinecone, ChromaDB, or Milvus for implementing semantic search and RAG. - Experience working within the Department of Defense (DoD) or Intelligence Community (IC). - Familiarity with deploying and managing applications in a secure government cloud environment. - Knowledge of prompt engineering techniques to optimize the performance and reliability of LLMs. Why CTC? - Our teams at CTC are passionate and thrive on collaboration in a team environment - When we encounter a difficult problem, we have a variety of talented and diverse employees that work together to solve the toughest challenges - Competitive salary and benefits package - Although our work at CTC is extremely important, we also recognize the need for our employees to maintain a proper mix of work and personal life - Visit www.ctc.com to learn more Join us! CTC offers exceptional career growth, cutting edge technology, educational opportunities, and recognition for quality work. https://concurrent-technologies-corporation.breezy.hr/ Staffing Requisition: SR# 2025-0140 “We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability status, protected veteran status, or any other characteristic protected by law.”

• Own the technical enablement of OpenAI products, including ChatGPT Enterprise, Codex, Agents, and API capabilities, helping define effective enablement patterns that support adoption across customer segments. • Lead customer training and enablement across the full customer lifecycle, from initial onboarding through expansion, optimization, and long-term adoption. • Design and deliver high-impact training engagements, including onboarding sessions, advanced capability trainings, executive briefings, hackathons, and hands-on workshops for audiences ranging from senior leaders to working teams. • Drive customer activation, sustained usage, and measurable business value through structured enablement and deployment programs designed for durable adoption at scale. • Partner closely with Sales, AI Success Engineers, Solutions Engineering, and Product teams to ensure seamless handoff from pre- to post-sale and consistent customer experience. • Develop and refine reusable training assets, playbooks, and best practices based on patterns observed across customers and regions. • Gather customer feedback from training and enablement engagements, synthesize themes across accounts, and relay insights to internal stakeholders to inform product and program improvements.