Transformation Engineer

TribalScale

14h

About The Position

TribalScale is seeking a Transformation Engineer to join its growing team and work as an embedded partner with a client organization of approximately 500 employees over an extended engagement. The role combines hands-on AI platform engineering, technical leadership, and organizational education. The engineer will establish and improve the client’s AI knowledge foundation, build production-ready agentic systems, advance Claude Code practices, and help teams across the organization adopt AI workflows.

This is an engineering and organizational transformation role requiring ownership from discovery and prototyping through production deployment, maintenance, and iterative improvement. The successful candidate will build secure, maintainable, useful systems that are widely adopted; partner with technical and business stakeholders; establish practical AI governance; and help the organization develop sustainable internal capabilities.

The first few months will involve building trusted relationships with client and TribalScale teams, understanding the client’s operating environment, and contributing working software to a meaningful business challenge. Over time, the role will include translating loosely defined needs into technical plans, delivering reliable AI-enabled products, establishing evaluation and observability practices, improving agent behavior and safeguards, teaching responsible operation, and creating reusable patterns for future TribalScale engagements.

Requirements

• Strong hands-on software or AI engineering experience, 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 personally built workflows, skills, subagents, MCP integrations, or harnesses.
• Proven ownership of production agent harnesses, including evaluations, observability, guardrails, debugging, maintenance, and continuous improvement.
• 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 adoption and change management.
• Ability to teach, with 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.

Nice To Haves

• 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.

Responsibilities

• Design, build, and maintain an LLM-powered company knowledge base or LLM wiki that captures institutional knowledge and makes it usable by employees and agents.
• Architect agentic memory and context strategies, including what agents remember, how knowledge is retrieved and refreshed, and how access permissions are enforced.
• Develop retrieval, indexing, knowledge-quality, and lifecycle processes to keep information accurate, relevant, and secure.
• Design, build, deploy, and operate agentic applications and production harnesses, including evaluations, observability, guardrails, testing, human oversight, and ongoing iteration.
• Establish Claude Code conventions for CLAUDE.md, skills, subagents, hooks, MCP integrations, and repeatable team workflows.
• Build reusable developer tooling, integrations, APIs, and automation to improve engineering productivity and software delivery.
• Deploy and maintain solutions on AWS, applying IAM permissions, security controls, monitoring, reliability practices, and cost management.
• Design and deliver a structured AI training program for an approximately 500-person organization, 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 integrate new practices into day-to-day work.
• Define and monitor adoption and impact measures, including active usage, workflow uptake, proficiency, productivity, and feedback, and improve the program based on results.
• 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 for 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.
• Translate loosely defined client needs into executable technical plans and deliver AI-enabled products that work reliably beyond controlled demonstrations.
• Establish practices that make quality measurable and regressions visible, and improve agent behavior by refining harnesses, loops, tools, graphs, context, and safeguards.
• Help client teams understand AI system capabilities, failure modes, and responsible operating practices.
• Create reusable technical patterns for future TribalScale engagements and help promising ideas reach production.

Benefits

• Work on high-impact challenges across industries and technology domains.
• Build real products and production systems, rather than only 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 client outcomes and TribalScale’s evolving technical practices.
• Join an environment that encourages ownership, diverse perspectives, and thoughtful innovation.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed