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TribalScale

Agile digital transformation and product development

Forward Deployed Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USANo salary listed

About the Job

Requirements

  • Professional experience building and deploying production-grade software, ideally including AI-powered or agentic systems.
  • Strong proficiency in Python, TypeScript, or another language commonly used to build AI applications, platforms, and developer tooling.
  • A practical understanding of harness engineering, including 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.
  • Understanding of trade-offs involving prompts, context management, memory, retrieval, tool use, structured outputs, and model selection.
  • 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 quickly understand unfamiliar systems, technologies, and business domains.
  • Ability to move from an ambiguous customer problem to a working prototype, validate it with real users and evaluations, and evolve it into a secure, maintainable production system.
  • Strong product judgment and the ability to balance model capability, reliability, latency, cost, security, and user experience.
  • Experience collaborating directly with customers, stakeholders, or cross-functional delivery teams.
  • Ability to explain AI-system behavior, limitations, risks, and technical trade-offs clearly in writing and verbally.
  • Ability to work in fast-moving environments where requirements and technical constraints continue to evolve.
  • Ability to travel occasionally for client workshops or on-site delivery, where required.

Responsibilities

  • Partner directly with clients to understand their objectives, workflows, technical environments, data, and operational constraints.
  • 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.
  • Create evaluation frameworks that measure task completion, accuracy, reliability, safety, latency, cost, and user value.
  • Develop rapid prototypes and proofs of concept, validate them with real users and representative evaluations, and evolve successful ideas into secure, scalable products.
  • 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.
  • Implement safeguards, permission boundaries, approval steps, and fallbacks for autonomous and semi-autonomous systems.
  • Instrument AI applications so teams can inspect traces, understand intermediate states, diagnose failures, and improve system performance.
  • Identify and address failure modes such as hallucinations, looping, brittle tool calls, context loss, prompt injection, non-deterministic behavior, and unsafe actions.
  • Troubleshoot complex technical and operational issues in client environments.
  • Communicate technical decisions, risks, trade-offs, and progress to technical and non-technical audiences.
  • Collaborate with product managers, designers, engineers, data specialists, security teams, and client stakeholders throughout the delivery lifecycle.
  • Establish engineering practices including automated testing, documentation, observability, security, and continuous delivery.
  • Capture reusable patterns, components, and insights that strengthen TribalScale’s engineering capabilities and future client engagements.
  • Support technical discovery, solution demonstrations, workshops, and pre-sales conversations when needed.

Desired Qualifications

  • Experience with agent frameworks, workflow engines, coding agents, or custom model-orchestration systems.
  • Experience creating tool interfaces, execution sandboxes, permission models, and human-in-the-loop controls for autonomous or semi-autonomous systems.
  • Familiarity with retrieval-augmented generation, embeddings, vector search, knowledge graphs, fine-tuning, and model-routing strategies.
  • Experience evaluating AI systems using golden datasets, simulators, adversarial testing, online experiments, and production feedback.
  • Familiarity with AI observability, including traces, token and cost analysis, latency measurement, failure classification, and quality dashboards.
  • Experience building systems that use multiple models or specialized agents to complete complex tasks.
  • Understanding of AI security concerns, including prompt injection, data leakage, excessive agency, insecure tool use, and supply-chain risks.
  • Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
  • Experience with containers, Kubernetes, infrastructure as code, and CI/CD tooling.
  • Contributions to AI infrastructure, evaluation tooling, agent frameworks, or related open-source projects.
  • Experience working in regulated or complex enterprise environments.
  • Experience in consulting, professional services, solutions engineering, sales engineering, or another customer-facing technical role.
  • A history of taking products from initial discovery through production launch and ongoing adoption.
  • Claude Certified Architect - Foundations or Professional certification (or equivalent), with practical experience designing and implementing Claude-based AI solutions, agentic workflows, and enterprise integrations.
  • Experience with agentic AI and harness-driven development, including designing, building, and optimizing autonomous AI agents, multi-agent workflows, tool integrations, and agent harnesses that support reliable, scalable, and production-ready AI applications.

About the Company

TribalScale

Agile digital transformation and product development

TribalScale helps large organizations navigate the digital era by applying Agile methods to transform teams, build digital products, and incubate new ventures. Its work includes redesigning and modernizing OTT offerings for media clients so users can access breaking news and other content through digital channels. The company combines consulting, product development, and partnerships to enable enterprise-wide change—from process improvements and brand development to backend support. What sets TribalScale apart is its collaborative approach: it provides strategic guidance, mentorship, and access to a network of technology partners to accelerate delivery and growth, rather than just advice or one-off projects. The goal is to help enterprises grow their digital capabilities, launch successful products, and create/scale disruptive ideas in ways that align with their business objectives.

Company size
11-50
Company stage
Not listed
Total funding
$2.6M
Headquarters
Toronto, Canada
Founded
2015

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