• Act as a trusted advisor to clients, prospects and partners, engaging at senior levels to quickly understand their technology ecosystems, operational challenges, and business goals. • Collaborate with clients and vendors on innovative solutions that integrate WideOrbit’s products with third-party tools, data sources, and workflows. • Lead discovery engagements to identify business objectives, operational challenges, technical requirements, and success criteria. • Develop consensus with clients on quantifiable success metrics for each engagement, ensuring that WideOrbit’s internal measures of value align with the clients. • Occasionally lead or support client-facing demonstrations, translating complex technical capabilities into clear, business-focused value. • Develop solutions and workflows tailored to meet unique client business objectives, either fully contained within the WideOrbit ecosystem or as part of a larger, integrated stack. • Map client’s existing business processes, workflows, and associated costs, identifying high leverage opportunities and prioritizing those in project planning. • Provide technical guidance, subject matter expertise, and product knowledge during sales engagements supporting complex deal negotiations and renewals. • Orchestrate the solution implementation process, ensuring smooth adoption, addressing technical and operational gaps, all while architecting the next phase of the solution. • Work closely with Sales, Product, Engineering, and Professional Services teams to align client priorities, market demands, and growth strategies. • Collaborate on strategies to enhance client satisfaction, identify revenue opportunities, and ensure successful long-term partnerships. • Maintain expertise in media, advertising technology, and operational workflows to ensure solutions meet industry challenges and trends. • Identify opportunities for product enhancements or integrations, advocating for innovation based on client feedback and market needs. • Partner with internal teams to evolve WideOrbit’s offerings, maintaining a leadership position in the ad tech ecosystem.

• Lead discovery with business and technology partners to understand objectives, constraints, current-state systems, and integration points. • Document current-state architecture and define target-state designs including system context diagrams, component designs, integration patterns, and data flows. • Design and modernize applications into cloud-compatible or cloud-native architectures using microservices, serverless, and event-driven patterns where appropriate. • Create strategies, roadmaps, and migration designs for transitioning applications and data workloads to cloud platforms. • Design AI and ML-enabled solutions, including model integration into products and business processes, and patterns for scalable inference and low-latency serving where needed. • Design Generative AI solution patterns, such as retrieval-augmented generation, tool and API integration, prompt and context management, and evaluation approaches. • Define reference architectures for AI platforms and enabling capabilities, such as data pipelines, feature and embedding generation, vector storage, model endpoints, and integration with enterprise APIs. • Establish best practices for MLOps and AI operations, including model versioning, deployment, monitoring, drift detection, incident response, and cost management. • Incorporate security-by-design practices into architectures, including identity and access controls, encryption, secrets management, secure networking, and audit logging. • Partner with governance and risk stakeholders to ensure responsible AI considerations are incorporated, including privacy, explainability, safety, compliance, and model risk controls as applicable. • Drive alignment and adoption of proposed solutions by clearly communicating tradeoffs, risks, and value and obtaining stakeholder alignment and governance approvals. • Support teams responsible for testing and validation and help triage and resolve design-related issues found during development, UAT, or production. • Perform other duties as assigned.

• Responsibility for the successful implementation of our software solutions for clients in the German-speaking and international markets • Work in small, well-established teams with a high degree of autonomy and short decision-making paths • Develop viable concepts for the digitization and automation of Finance and Procurement processes • Guide customers through change and transformation processes • Actively contribute to internal initiatives, such as project management standards and new tools

Role Description We are looking for a motivated Software Engineer to join our team and help build AI agents that solve real-world problems for customers and employees alike. You will work closely with senior engineers and product partners to design, develop, test, and maintain backend services and AI-driven workflows. This role is ideal for someone early in their career who is passionate about Python, agentic workflows, and learning best engineering practices in a high-growth field. What You Will Do: - Agent Development: Contribute to the development of AI agents, prompt engineering, and supporting backend infrastructure. - Clean Code: Write clean, well-structured, and maintainable Python code that follows established coding standards within the team. - Quality Assurance: Implement unit tests and integration tests to ensure agent reliability and prevent regressions. - Workflow: Use Git and CI/CD tools effectively within a collaborative team environment. - Agile Participation: Engage in Scrum ceremonies, contributing to sprint planning and retrospectives. - Troubleshooting: Debug and troubleshoot issues in development and production, specifically focusing on the unique challenges of LLM outputs. - Peer Growth: Collaborate with team members through code reviews, focusing on learning and maintaining high code quality. Qualifications - Python Proficiency: Strong foundational coding skills in Python (familiarity with asyncio or FastAPI is a plus). - Problem Solving: Solid analytical and debugging skills, especially when dealing with complex data structures or APIs. - Core Fundamentals: Solid understanding of data structures, RESTful APIs, and backend service architecture. - Engineering Rituals: Familiarity with Git workflows and a strong understanding of why we do code reviews. - Testing Mindset: Experience with testing frameworks (like pytest) and an understanding of test-aware development. - Agile Experience: Comfortable working in a fast-paced, iterative Agile environment. - Growth Mindset: An eagerness to learn new technologies, ask "why," and take ownership of your professional growth. Nice to Have: - AI/LLM Interest: Exposure to LLMs or agent frameworks. - Infrastructure: Familiarity with cloud platforms and Docker/containerization. - Data Handling: Experience with asynchronous processing or message queues. Requirements - Education: Bachelor's Degree (preferred, but a combination of coursework and experience may be considered). - Relevant Work Experience: 5-7 Years. Compensation - Primary Location Pay Range: $142,651.46 - $213,977.19. - Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. - Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. - Comcast provides best-in-class Benefits to eligible employees.