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Transformation Engineer

TribalScale · Remote USA · United States

Remote Posted Open until 26 Oct 2026
  • Remote Remote USA — job location

The job, in the employer's words

Shape the Future with TribalScale

TribalScale is a digital innovation firm that helps organizations adapt and thrive in a rapidly changing world. We partner with clients to build transformative digital products, modernize technology platforms, and apply emerging technologies—including artificial intelligence—to meaningful business challenges.
Our teams work closely with clients from strategy through execution. We value curiosity, ownership, practical innovation, and people who are comfortable turning ambiguity into action.

Our Digital Expertise

  • Transformation Experts: We transform traditional business models into agile, AI-powered ecosystems.
  • Strategic Visionaries: We navigate the uncharted waters of technological evolution.
  • Product Virtuosos: We orchestrate the creation of world-class digital solutions.
  • Code Optimizers: We leverage AI to refine and perfect digital systems.

Our Technological Toolkit

  • Mobile & Web Development: (iOS, Android, React Native, React, Node.js)
  • Voice-Activated Platforms: (Amazon Alexa, Google Home)
  • Connected Ecosystems: (Cars and Homes)
  • Streaming Platforms: (Roku, Fire TV, Android TV, tvOS)

The TribalScale Professional

You thrive in challenging environments where innovation is key. Your passion for technology is matched only by your drive to redefine its limits. You seek more than a job; you seek a calling—a chance to make a lasting impact on the digital landscape.

The Opportunity

We’re looking for a Transformation Engineer to join our growing team at TribalScale. In this role, you will be embedded with a client organization of approximately 500 employees, serving as a hands-on AI platform builder, technical leader, and educator over an extended engagement.

You will help establish and continuously improve the organization’s AI knowledge foundation—its “company brain”—while building production-ready agentic systems, advancing Claude Code practices, and enabling teams across the business to adopt AI workflows. Success means not only shipping working systems, but also making them secure, maintainable, useful, and widely adopted.

This is a hands-on engineering and organizational transformation role for someone who can move quickly from ambiguity to production, partner across functions, and own outcomes over time.

What You’ll Do

AI Knowledge Systems & Agentic Memory

  • Design, build, and maintain an LLM-powered company knowledge base (“company brain” or LLM wiki) that captures institutional knowledge and makes it usable by employees and agents.
  • Architect agentic memory and context strategies: define what agents remember, how knowledge is retrieved and refreshed, and how access permissions are enforced.
  • Develop practical retrieval, indexing, knowledge-quality, and lifecycle processes that keep information accurate, relevant, and secure.

Production Agentic Engineering & Claude Code

  • Design, build, deploy, and operate agentic applications and production harnesses, including evaluations, observability, guardrails, testing, human oversight, and ongoing iteration.
  • Serve as the organization’s Claude Code expert: establish conventions for CLAUDE.md, skills, subagents, hooks, MCP integrations, and repeatable team workflows.
  • Build reusable developer tooling, integrations, APIs, and automation that improve engineering productivity and software delivery.
  • Deploy and maintain solutions on AWS, applying IAM permissions, security controls, monitoring, reliability practices, and cost management.

Organization-Wide Enablement & Adoption

  • Design and deliver a structured training program for an approximately 500-person organization, covering agentic memory, harnesses, Claude Code, and practical AI workflows for technical and non-technical audiences.
  • Run workshops, hands-on demonstrations, office hours, and tailored onboarding; create documentation and reusable learning materials.
  • Develop internal AI champions and support managers and teams as they embed new practices into day-to-day work.
  • Define and monitor adoption and impact measures, such as active usage, workflow uptake, proficiency, productivity, and feedback; improve the program based on results.

Long-Term Transformation & Delivery

    • Partner with stakeholders across engineering, IT, security, and business functions to prioritize use cases and align technical work with organizational needs.
    • Own solutions from discovery and rapid prototyping through production deployment, maintenance, and iterative improvement.
    • Establish practical AI governance covering data access, privacy, security, reliability, and responsible use across hundreds of users.
    • Balance speed, quality, maintainability, and change management while helping the organization build sustainable internal capabilities.

What You Bring

  • 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, with specific examples of workflows, skills, subagents, MCP integrations, or harnesses you have personally built.
  • Proven ownership of production agent harnesses, including evaluations, observability, guardrails, debugging, maintenance, and continuous improvement—not just familiarity with the concepts.
  • Strong AWS experience, including relevant services such as 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 the human side of adoption and change management.
  • Proven ability to teach: experience running workshops, building training curricula, or onboarding teams to new tools, and explaining technical ideas to non-engineers.
  • Ability to partner across technical and business teams, independently own initiatives, and deliver practical solutions in fast-paced environments.
We recognize that strong candidates may not meet every qualification listed. If this role excites you and your experience is adjacent to what we have described, we encourage you to apply.

Nice to Have

  • Experience leading AI adoption or platform transformation in a mid-sized organization, particularly one with approximately 200–2,000 employees.
  • Experience with LangGraph, LangChain, or other agent orchestration and evaluation frameworks.
  • Claude Certified Architect certification or other relevant AI engineering credentials.
  • Experience building internal communities of practice, champion networks, or measurable enterprise enablement programs.
  • Experience with CI/CD, DevOps, infrastructure as code, and operating secure AI systems at organizational scale.

What Success Looks Like

In your first few months, you will have built trusted relationships with client and TribalScale teams, developed a strong understanding of the client’s operating environment, and contributed working software to a meaningful business challenge.

As you grow in the role, you will:
  • Turn loosely defined client needs into clear, executable technical plans.
  • Deliver AI-enabled products that perform reliably outside of controlled demonstrations.
  • Establish evaluation and observability practices that make quality measurable and regressions visible.
  • Improve agent behavior by refining harnesses, loops, tools, graphs, context, and safeguards—not only by changing prompts or models.
  • Help client teams understand what their AI systems can do, where they can fail, and how they should be operated responsibly.
  • Create reusable technical patterns that accelerate future TribalScale engagements.
  • Become a trusted partner who can navigate uncertainty, solve difficult technical problems, and help promising ideas reach production.

Why TribalScale

  • 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.
  • Join an environment where ownership, diverse perspectives, and thoughtful innovation are encouraged.

Why Choose TribalScale

At TribalScale, collaboration is at the heart of our innovative approach. We don't simply work for clients; we form partnerships, building transformative solutions that redefine what's possible. Our team, once at the forefront of the mobile revolution, now leads the charge in AI-driven innovation.

We empower each team member to be a catalyst for change, adhering to our principles of meritocracy, empowerment, and transparency. Diversity isn't just celebrated—it's fundamental to our strength. Our mission to "Right the Future" is a call to action to make a significant impact in the world of innovation.

 

Diversity: Our Collective Strength

TribalScale proudly stands as a beacon of equal opportunity in employment and workplace culture. We are steadfastly committed to equal employment opportunity, transcending the boundaries of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, able-bodiedness, or gender identity.

We not only welcome but actively encourage applications from individuals of all abilities, ages, citizenships, marital statuses, and gender identities. Your unique perspective is the key to our collective innovation.

Should you require any accommodations, we implore you to inform us. Our commitment to inclusivity knows no bounds, and we stand ready to adapt our processes to ensure your comfort and success.

 

Requirements mentioned

  • 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, with specific examples of workflows, skills, subagents, MCP integrations, or harnesses you have personally built.
  • Proven ownership of production agent harnesses, including evaluations, observability, guardrails, debugging, maintenance, and continuous improvement—not just familiarity with the concepts.
  • Strong AWS experience, including relevant services such as 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 the human side of adoption and change management.
  • Proven ability to teach: experience running workshops, building training curricula, or onboarding teams to new tools, and explaining technical ideas to non-engineers.
  • Ability to partner across technical and business teams, independently own initiatives, and deliver practical solutions in fast-paced environments.
  • We recognize that strong candidates may not meet every qualification listed. If this role excites you and your experience is adjacent to what we have described, we encourage you to apply.
  • Experience leading AI adoption or platform transformation in a mid-sized organization, particularly one with approximately 200–2,000 employees.
  • Experience with LangGraph, LangChain, or other agent orchestration and evaluation frameworks.
  • Claude Certified Architect certification or other relevant AI engineering credentials.
  • Experience building internal communities of practice, champion networks, or measurable enterprise enablement programs.
  • Experience with CI/CD, DevOps, infrastructure as code, and operating secure AI systems at organizational scale.

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