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Technical Track

AI Training for Engineers

Hands-On AI Engineering Skills for Your Software Teams

A technical, code-first AI training programme for software engineers and development teams. Learn to integrate LLM APIs, build RAG pipelines, fine-tune models, and ship AI features into production applications your company already runs.

4–8 Weeks
On-site / Virtual
Intermediate to Advanced
Teams of 10–40
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What You Get

LLM API integration into existing codebases
RAG pipelines using your own company documentation
Fine-tuning and evaluation for domain-specific tasks
CI/CD and observability for AI-powered features
Code reviews with CraftVoy AI engineers
Capstone: AI feature shipped to a staging environment

Who Is This For

  • Software engineering teams adding AI features to products
  • Backend and full-stack developers new to LLM integration
  • Engineering leads planning an AI feature roadmap
  • Teams migrating from AI prototypes to production systems

Learning Outcomes

  • Ship production-ready AI features into your existing applications
  • Build and maintain RAG pipelines on internal company data
  • Apply engineering best practices to AI-specific challenges
  • Reduce reliance on external consultants for AI feature work

Curriculum

1

Module 1: LLM Integration Fundamentals

  • Working with major LLM provider APIs
  • Streaming, function calling and structured output
  • Cost and latency-aware architecture decisions
2

Module 2: RAG & Knowledge Systems

  • Vector databases and embedding pipelines
  • Chunking, retrieval and re-ranking strategies
  • Building RAG on your company's own data
3

Module 3: Production Readiness

  • Testing, evaluation and guardrails for AI features
  • Observability, logging and cost monitoring
  • CI/CD pipelines for AI-powered services

Frequently Asked Questions

What is the prerequisite for engineers?

Working proficiency in at least one major programming language (Python, JavaScript/TypeScript, Java) is required. No prior AI experience needed.

Can we use our own codebase for exercises?

Yes — where feasible, we adapt labs to your company's tech stack so engineers practice on realistic scenarios.

Do you cover fine-tuning?

Yes — an advanced module covers LoRA/QLoRA fine-tuning and evaluation for teams that need domain-specific model behaviour.

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Ready to get started?

Talk to a CraftVoy advisor today and find the right batch for your schedule.

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