Role overview

TribalScale is seeking a Forward Deployed Agile Software Engineer to work embedded with clients, bridging software engineering, artificial intelligence, and product delivery. In this position, you will partner directly with clients to understand complex business challenges, design solutions, and deploy production-quality software that creates immediate, measurable impact. You will operate as both a hands-on engineer and a technical strategist, helping clients make informed technology decisions while building AI-enabled systems that work reliably in real-world environments.

Key responsibilities

Work directly with clients to understand their business objectives, technical environments, data sources, and operational constraints.
Translate business challenges into clear technical requirements, solution architectures, and delivery plans.
Design and build AI-enabled applications, agentic workflows, APIs, data pipelines, and full-stack products that integrate with client systems and enterprise data sources.
Engineer the infrastructure surrounding AI models, including prompt design, tool integration, context management, permissions, runtime controls, and observability systems.
Build and refine agent loops that handle planning, tool selection, execution, observation, reflection, recovery, and appropriate termination.
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 evolve successful solutions into secure, scalable products.
Implement safeguards, permission boundaries, approval steps, and fallbacks for autonomous and semi-autonomous systems to ensure safe operation.
Instrument AI applications to enable teams to inspect traces, diagnose failures, and improve system performance.
Identify and address failure modes such as hallucinations, looping behavior, brittle tool calls, context loss, prompt injection, and unsafe actions.
Troubleshoot complex technical and operational issues in client environments and communicate technical decisions and trade-offs to both technical and non-technical audiences.
Collaborate with product managers, designers, engineers, data specialists, security teams, and client stakeholders throughout delivery.
Establish strong engineering practices including automated testing, documentation, observability, security, and continuous delivery.
Capture reusable patterns and components that strengthen the firm’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 for building AI applications, platforms, and developer tooling.
Practical understanding of harness engineering: 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, 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, and human review processes.

What makes this role worth considering

This position offers direct exposure to cutting-edge AI and product development work, with immediate visibility into how your engineering shapes real-world client outcomes. You will work at the intersection of strategy and execution, collaborating with experienced teams across product, design, and data disciplines. The embedded deployment model means you will see the full arc of discovery, design, and delivery while building systems that address ambiguous, high-stakes business challenges.