Forward Deployed Agile Software Engineer
New
T
TribalScaleAI software
Remote CanadaFull-TimeMiddle
Salary not disclosed
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Job Details
- Required Skills
- PythonTypeScriptRESTful APIsDistributed Systems
Requirements
- Have professional experience building and deploying production-grade software.
- Be proficient in Python, TypeScript, or another language commonly used for AI applications, platforms, and developer tooling.
- Understand harness engineering, including infrastructure, context, tools, permissions, controls, and feedback mechanisms for reliable AI agents.
- Have experience building or working with agent loops for planning, tool selection, execution, observation, reflection, recovery, and termination.
- Be familiar with graph-based orchestration, state machines, and multi-step workflows.
- Have experience designing AI evaluation systems, including task-based benchmarks, regression suites, model-graded evaluations, human review, and production monitoring.
- Understand trade-offs involving prompts, context management, memory, retrieval, tool use, structured outputs, and model selection.
- Have experience instrumenting AI systems to trace decisions, inspect intermediate states, measure quality, and diagnose failures.
- Have strong knowledge of APIs, distributed systems, databases, cloud infrastructure, and modern software-development practices.
- Be able to move from an ambiguous customer problem to a working prototype and evolve it into a secure, maintainable production system.
- Have experience collaborating directly with customers, stakeholders, or cross-functional delivery teams.
- Communicate technical decisions, AI-system behavior, limitations, risks, and trade-offs clearly to technical and non-technical audiences.
- Be able to travel occasionally for client workshops or on-site delivery, where required.
Responsibilities
- Partner with clients to understand objectives, workflows, technical environments, data, and operational constraints.
- Translate ambiguous business challenges into 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 AI-model harnesses, agent loops, workflow graphs, safeguards, and human approval controls.
- Create evaluation frameworks to measure task completion, accuracy, reliability, safety, latency, cost, and user value.
- Develop prototypes, validate them with users and evaluations, and evolve successful ideas into secure, scalable products.
- Integrate solutions with client systems, enterprise data sources, cloud platforms, and third-party services.
- Instrument AI applications, troubleshoot failures, and address issues such as hallucinations, context loss, and prompt injection.
- Collaborate with product, design, engineering, data, security, and client stakeholders throughout delivery.
- Establish engineering practices including automated testing, documentation, observability, security, and continuous delivery.
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