Remote AI Solutions Engineer

Tribalscale Inc.; San Francisco (CA); Remote; USD 150,000 - 210,000; Full time

Job summary

TribalScale is seeking a Forward Deployed Engineer to blend software engineering, AI, and client delivery. You will embed with client and internal teams to translate business needs into production-ready solutions and help shape AI-powered products in real-world environments.

Ideal candidates are hands-on engineers who thrive on discovery, communicate clearly with stakeholders, and own projects from concept to deployment, including designing systems, tooling, and safeguards for reliable AI

Qualifications

• Professional experience building production-grade software, ideally with AI-powered or agentic systems.
• Strong proficiency in Python, TypeScript, or similar languages used for AI apps and tooling.
• Practical understanding of harness engineering: context, tools, permissions, controls, and feedback for reliable AI agents.
• Experience with agent loops: planning, tool selection, execution, observation, reflection, recovery, termination.
• Familiarity with graph-based orchestration, state machines, and multi-step workflows coordinating agents, tools, data, and human approvals.

Responsibilities

• Partner directly with clients to understand objectives, workflows, environments, data, and constraints.
• Translate ambiguous challenges into clear technical requirements, architectures, and delivery plans.
• Design and build AI-enabled applications, agentic workflows, APIs, data pipelines, and full-stack products.
• Engineer harnesses around AI models, including prompts, tools, context, memory, permissions, and observability.

Skills

Python

TypeScript

AI applications

Agent loops

Cloud platforms

Tools

AWS

Kubernetes

Docker

CI/CD

APIs

Job description

TribalScale is seeking a Forward Deployed Engineer to blend software engineering, AI, and client delivery. You will embed with client and internal teams to translate business needs into production-ready solutions and help shape AI-powered products in real-world environments.

Ideal candidates are hands-on engineers who thrive on discovery, communicate clearly with stakeholders, and own projects from concept to deployment, including designing systems, tooling, and safeguards for reliable AI