AI Engineer Coach | Transitioning Software Teams to AI Engineering

Hands-On AI Engineer Coaching for Software Teams

Address the skill gap between backend/full-stack developers and AI engineering

Is your backend/full-stack engineering team embarking on building LLM apps/RAG/chatbots and unsure how best to transition to the world of AI engineering?

You're not alone.

Many engineering leaders find their software teams grappling with unfamiliar territory:

Implementing effective Retrieval-Augmented Generation (RAG) systems

Improving retrieval quality for more accurate results

Mastering the nuances of prompt engineering

Navigating the LLMOps landscape and finding the sweet spot for traceability and reproducibility

Learning how to efficiently setup and perform evals

Knowing which LLM to use and when to fine-tune models for optimal performance

My aim is to demystify AI and cut through the hype.

From improving prompts to productionizing LLMOps, I'll help you and your team make sound and informed decisions every step of the way.

🛠️ Player: Hands-On AI Engineer

I work alongside your team to build practical AI solutions:

🤖 Develop effective Retrieval-Augmented Generation (RAG) systems

💬 Create chatbots and co-pilots using the latest techniques and tactics

🎯 Ruthlessly focused on rapid delivery and quick time-to-value

🏋️ Coach: Mentoring Your Team's AI Journey

I help facilitate the shift from traditional software engineering to AI-centric approaches.

🧠 Provide applied training in current AI engineering techniques and best practices

🔀 Help your QA team understand how LLM evals are different from software QA

🚀 Mentor your engineering leaders to develop an intuition for what LLMs can and cannot do

🧭 Strategist: Navigating AI Decisions

I offer experienced-based guidance for your AI initiatives:

🏆 Advise on choosing frameworks/models for your projects

🎯 How to plan for success when it comes to LLM-based applications

🗺️ Use the power of LLMs to maximize business objectives