TribalScale

Full-stack Engineer

• Partner directly 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 covering prompts, tools, context, memory, permissions, runtime controls, observability, and feedback
• Build and refine agent loops for planning, execution, observation, reflection, recovery, and termination
• Model complex workflows using graphs, state machines, and orchestration patterns
• Create evaluation frameworks for task 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 user interfaces, backend services, AI infrastructure, data workflows, and deployment pipelines
• Implement safeguards, permission boundaries, approval steps, and fallbacks for autonomous systems
• Instrument AI applications to inspect traces, intermediate states, failures, and performance
• Identify and address 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
• Establish automated testing, documentation, observability, security, and continuous delivery practices
• Capture reusable patterns, components, and insights for future client engagements
• Support technical discovery, solution demonstrations, workshops, and pre-sales conversations
• Build trusted client and TribalScale relationships and contribute working software to meaningful business challenges

Explore Forward Deployed Agile Software Engineer at TribalScale. Review requirements and application details.

Forward Deployed Agile Software Engineer

• Partner directly with clients to understand objectives, workflows, technical environments, data, and 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 and graph/state-machine 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 evolve successful ideas into secure, scalable products
• Integrate solutions with client systems, enterprise data, cloud platforms, and third-party services
• Contribute across interfaces, backend services, AI infrastructure, data workflows, and deployment pipelines
• Implement safeguards, permissions, approval steps, and fallbacks
• Instrument AI applications to inspect traces, intermediate states, failures, and performance
• Troubleshoot technical and operational issues in client environments
• Communicate technical decisions, risks, trade-offs, and progress
• Collaborate with product managers, designers, engineers, data specialists, security teams, and clients
• Establish testing, documentation, observability, security, and continuous-delivery practices
• Capture reusable patterns and insights
• Support technical discovery, demonstrations, workshops, and pre-sales conversations

• Partner directly 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, 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 using graphs, state machines, and 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 technology stack, including interfaces, backend services, AI infrastructure, data workflows, and deployment pipelines
• Implement safeguards, permissions, approval steps, and fallbacks for autonomous systems
• Instrument AI applications for trace inspection, intermediate-state analysis, failure diagnosis, and performance improvement
• Identify and address hallucinations, looping, brittle tool calls, context loss, prompt injection, nondeterministic behavior, 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, solution demonstrations, workshops, and pre-sales conversations
• Build trusted client relationships, understand operating environments, and deliver working software for meaningful business challenges

• Partner directly 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 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 using graphs, state machines, and orchestration patterns
• Create evaluation frameworks measuring task 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 for autonomous and semi-autonomous systems
• Instrument AI applications to inspect traces, intermediate states, failures, and performance
• Identify and address 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
• Establish automated testing, documentation, observability, security, and continuous delivery practices
• Capture reusable patterns, components, and insights for future engagements
• Support technical discovery, solution demonstrations, workshops, and pre-sales conversations
• Build trusted client and TribalScale relationships and contribute working software to meaningful business challenges

• 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