TribalScale is a digital innovation firm that helps organizations adapt and thrive in a rapidly changing world. We partner with clients to build transformative digital products, modernize technology platforms, and apply emerging technologies—including artificial intelligence—to meaningful business challenges. Our Digital Expertise Transformation Experts: We transform traditional business models into agile, AI-powered ecosystems. We navigate the uncharted waters of technological evolution. We orchestrate the creation of world-class digital solutions. We leverage AI to refine and perfect digital systems. Mobile & Web Development: (iOS, Android, React Native, React, Node.js) Cars and Homes) Roku, Fire TV, Android TV, tvOS) you seek a calling—a chance to make a lasting impact on the digital landscape. TribalScale is looking for a Forward Deployed Engineer to work at the intersection of software engineering, artificial intelligence, product development, and client delivery. In this role, you will embed with client and internal teams to understand complex business problems, rapidly design solutions, and deploy production-quality software in real-world environments. You will operate as both a hands-on engineer and a trusted technical partner—translating business needs into working products while helping clients make sound technology decisions. You will help design the systems around AI models: the harnesses, agent loops, state graphs, tools, context, evaluations, observability, permissions, and human controls required to make AI applications useful and reliable in production. This role is ideal for an adaptable engineer who enjoys direct customer interaction, can move comfortably between discovery and delivery, and wants to see their work create immediate, measurable impact.



Partner directly with clients to understand & inform their objectives, workflows, technical environments, data, and operational constraints. Provide expert advice on architecture, data layers and data pipelines, helping to structure the underpinning of automated delivery cycles Translate ambiguous business challenges into clear technical requirements, solution architectures, prototypes, and delivery plans. Design and build AI-enabled applications, agentic workflows, developer tools, APIs, data pipelines, and full-stack products. Engineer the harnesses around AI models, including prompts, tools, context, memory, permissions, runtime controls, observability, and feedback mechanisms. Build and refine agent loops that support planning, tool selection, execution, observation, reflection, recovery, and termination. Model complex workflows as graphs, state machines, or other orchestration patterns that coordinate models, tools, data, systems, and human approvals. Integrate solutions with client systems, enterprise data sources, cloud platforms, and third-party services. Work across the technology stack, contributing wherever needed—from user interfaces and backend services to AI infrastructure, data workflows, and deployment pipelines. Instrument AI applications so teams can inspect traces, understand intermediate states, diagnose failures, and improve system performance. Troubleshoot complex technical and operational issues in client environments.



Communicate technical decisions, risks, trade-offs, and progress clearly to both technical and non-technical audiences. Collaborate with product managers, designers, engineers, data specialists, security teams, and client stakeholders throughout the delivery lifecycle. Establish solid engineering practices, including automated testing, documentation, observability, security, and continuous delivery. Support technical discovery, solution demonstrations, workshops, and pre-sales conversations when needed. Professional experience building and deploying production-grade software, including AI-powered or agentic systems. Robust proficiency in Python, TypeScript, or another language commonly used to build AI applications, platforms, and developer tooling. A practical understanding of harness engineering: designing the infrastructure, context, tools, permissions, controls, and feedback mechanisms that enable AI agents to operate reliably. Experience building or working with agent loops, including planning, tool selection, execution, observation, reflection, recovery, and termination. Familiarity with graph-based orchestration, state machines, and multi-step workflows for coordinating agents, tools, data, and human approvals. Experience designing evaluation systems for AI applications, including task-based benchmarks, regression suites, model-graded evaluations, human review, and production monitoring. Experience instrumenting AI systems to trace decisions, inspect intermediate states, measure quality, and diagnose failures. Strong knowledge of APIs, distributed systems, databases, cloud infrastructure, and modern software-development practices. Ability to move from an ambiguous customer problem to a working

📌 Senior Agentic Engineer (Canada)
🏢 Urban Ridge Supplies
📍 Canada