Role overview

TribalScale is a digital innovation firm that partners with organizations to build transformative products, modernize technology platforms, and apply artificial intelligence to business challenges. As a Forward Deployed Engineer, you will embed directly with client teams to understand complex problems, design solutions, and deploy production-quality AI-enabled software in real-world environments.

Key responsibilities

Partner with clients to understand their business objectives, workflows, technical environments, data constraints, and operational needs.
Translate ambiguous business challenges into clear technical requirements, solution architectures, prototypes, and delivery roadmaps.
Design and build AI-enabled applications, agentic workflows, developer tools, APIs, data pipelines, and full-stack products that solve client problems.
Engineer the infrastructure around AI models, including prompt design, tool integration, context management, permissions, runtime controls, observability, and feedback mechanisms.
Build and refine agent loops that support planning, tool selection, execution, observation, reflection, recovery, and appropriate 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 in production environments.
Develop rapid prototypes and proofs of concept, validate them with real users and representative evaluations, then evolve successful ideas into secure, scalable products.
Integrate solutions with client systems, enterprise data sources, cloud platforms, and third-party services.
Implement safeguards, permission boundaries, approval steps, and fallbacks for autonomous and semi-autonomous systems.
Instrument AI applications to enable teams to inspect traces, understand intermediate states, diagnose failures, and improve performance.
Identify and address failure modes including hallucinations, looping, brittle tool calls, context loss, prompt injection, and unsafe actions.
Troubleshoot complex technical and operational issues in client environments and communicate trade-offs and progress 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 strong engineering practices including automated testing, documentation, observability, security, and continuous delivery.
Capture reusable patterns, components, and insights that strengthen the organization’s engineering capabilities for future engagements.

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.
Practical understanding of harness engineering, including designing 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, and recovery processes.
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, and human review processes.

What makes this role worth considering

This position offers the opportunity to work at the intersection of software engineering, artificial intelligence, and product development while maintaining direct client relationships. You will see your work create immediate, measurable impact by embedding with teams and translating their most complex challenges into working solutions in production environments.