Transformation Engineer

TribalScale

. Build and maintain an LLM-powered company knowledge base or “company brain” .

Posted 10/23/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining LLM-powered knowledge management systems, with strong proficiency in Python, TypeScript, and AWS solutions. Capable of leading AI adoption initiatives and delivering training to enhance organizational capabilities in AI technologies.

Highest-signal resume keywords

LLM Knowledge ManagementPython ProgrammingAWS Solutions ArchitectureClaude Code ExpertiseAI Adoption Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonTypeScriptJavaScriptLLM Retrieval SystemsAgentic Memory DesignAWS LambdaAWS IAMOpenSearchCI/CDDevOps

Soft Skills

Technical CommunicationChange ManagementWorkshop FacilitationCross-Functional CollaborationProblem Solving

Tools & Technologies

Claude CodeMCP IntegrationsVector SearchLangGraphLangChain

Certifications & Qualifications

Claude Certified Architect

Industry Keywords

AI EngineeringKnowledge ManagementInformation LifecycleData GovernanceEnterprise Search

Tech Stack

Tools & technologies

AWSJavaScriptPythonTypeScript

About the role

Key responsibilities & impact

Build and maintain an LLM-powered company knowledge base or “company brain”
Architect agentic memory, context strategies, retrieval, knowledge refresh, and access permissions
Develop retrieval, indexing, knowledge-quality, and information lifecycle processes
Design, build, deploy, and operate production agentic applications and harnesses
Establish Claude Code conventions for CLAUDE.md, skills, subagents, hooks, MCP integrations, and team workflows
Build developer tooling, integrations, APIs, and automation to improve engineering productivity
Deploy and maintain AWS solutions using IAM, security controls, monitoring, reliability practices, and cost management
Design and deliver AI training for an approximately 500-person organization
Run workshops, demonstrations, office hours, onboarding, and create documentation and learning materials
Develop AI champions and support managers and teams adopting new practices
Define and monitor AI adoption and impact measures
Partner with engineering, IT, security, and business stakeholders to prioritize use cases
Own solutions from discovery and prototyping through production, maintenance, and iterative improvement
Establish AI governance for data access, privacy, security, reliability, and responsible use
Turn ambiguous client needs into technical plans and deliver reliable AI-enabled products
Establish evaluation and observability practices and refine agent harnesses, tools, graphs, context, and safeguards
Create reusable technical patterns for future TribalScale engagements

Requirements

What you’ll need

Strong hands-on software or AI engineering experience, with proficiency in Python, TypeScript, JavaScript, or comparable languages, and experience delivering production systems
Demonstrable experience building LLM knowledge management or retrieval systems, such as RAG, LLM wikis, enterprise search, or related context-engineering solutions
Practical expertise designing agentic memory, retrieval strategies, context management, and permission-aware knowledge access
Deep, demonstrable Claude Code expertise, including workflows, skills, subagents, MCP integrations, or harnesses personally built
Proven ownership of production agent harnesses, including evaluations, observability, guardrails, debugging, maintenance, and continuous improvement
Strong AWS experience, including Lambda, Bedrock, IAM, S3, and vector search or OpenSearch, with attention to security, scalability, and cost
Experience working within an organization undergoing significant technology or AI transformation, including adoption and change management
Experience running workshops, building training curricula, or onboarding teams to new tools
Ability to explain technical ideas to non-engineers
Ability to partner across technical and business teams, independently own initiatives, and deliver practical solutions in fast-paced environments
Nice to have: experience leading AI adoption or platform transformation in a 200–2,000 employee organization
Nice to have: experience with LangGraph, LangChain, or other agent orchestration and evaluation frameworks
Nice to have: Claude Certified Architect certification or other relevant AI engineering credentials
Nice to have: experience with CI/CD, DevOps, infrastructure as code, and secure AI systems at organizational scale

Benefits

Comp & perks

Work on high-impact challenges across industries and technology domains
Build real products and production systems—not just recommendations or presentations
Work directly with clients and see the impact of your decisions
Explore emerging approaches to AI, agentic systems, product development, and software delivery
Collaborate with multidisciplinary teams that value experimentation and continuous learning
Influence both client outcomes and TribalScale’s evolving technical practices
Ownership, diverse perspectives, and thoughtful innovation encouraged
Equal employment opportunity and workplace inclusivity
Workplace accommodations available upon request