Forward Deployed Engineer building AI applications, agentic workflows, and production software for TribalScale’s digital innovation clients. Partnering directly with customers from discovery through deployment.
Responsibilities
Partner directly with clients to understand objectives, workflows, technical environments, data, and operational constraints
Translate ambiguous business challenges into technical requirements, 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, including prompts, tools, context, memory, permissions, runtime controls, observability, and feedback mechanisms
Build and refine agent loops for planning, tool selection, execution, observation, reflection, recovery, and termination
Model complex workflows as graphs, state machines, or orchestration patterns
Create evaluation frameworks measuring completion, accuracy, reliability, safety, latency, cost, and user value
Develop prototypes and proofs of concept, 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
Contribute across the stack, including interfaces, backend services, AI infrastructure, data workflows, and deployment pipelines
Implement safeguards, permission boundaries, approval steps, and fallbacks
Instrument AI applications to inspect traces, intermediate states, failures, and performance
Identify and address hallucinations, looping, brittle tool calls, context loss, prompt injection, nondeterminism, and unsafe actions
Troubleshoot 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
Establish automated testing, documentation, observability, security, and continuous delivery practices
Capture reusable patterns, components, and insights for future engagements
Support technical discovery, demonstrations, workshops, and pre-sales conversations
Build trusted client relationships and contribute working software to meaningful business challenges
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
Experience building or working with agent loops
Familiarity with graph-based orchestration, state machines, and multi-step workflows
Experience designing evaluation systems for AI applications
Understanding of 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 understand unfamiliar systems, technologies, and business domains quickly
Ability to move from an ambiguous customer problem to a working prototype and production system
Strong product judgment balancing capability, reliability, latency, cost, security, and user experience
Experience collaborating directly with customers, stakeholders, or cross-functional delivery teams
Excellent written and verbal communication skills
Comfort working in fast-moving environments with evolving requirements and technical constraints
High degree of ownership, curiosity, empathy, and bias toward action
Ability to travel occasionally for client workshops or on-site delivery
Nice-to-have: agent frameworks, workflow engines, coding agents, or custom model-orchestration systems
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