Ignite Builder
Can put an agent in production Monday morning.
Ignite Builder is an AI Engineer. You build agentic systems that run reliably in production — not prototypes, not demos. You understand the full stack from LLM calls to observability dashboards, from prompt patterns to token economics.
Demand for developers who can put agents into operation is exploding, and supply is thin. Most claim to 'build something with AI'. Few can deliver it reliably. You become one of the few.
Typical client situations
Eksempler på når Ignite Builder-profilen er den riktige for kunden.
- 01The client has an AI idea that works as a prototype but needs to be in actual production with users
- 02The client needs to build an agent that performs tasks (not just answers) against internal systems and data
- 03The client must replace a manual step with something that handles edge cases and failures gracefully
- 04The client wants to connect AI to their own systems via APIs, MCP or custom integrations
Core skills
- LLM app engineering: structured outputs, tool use, streaming, multi-turn state
- Agent orchestration (LangGraph, Pydantic AI, multi-agent patterns)
- Model Context Protocol (MCP) as integration layer to enterprise data and actions
- RAG engineering: chunking, hybrid search, re-ranking, retrieval evaluation
- Eval CI: regression testing of prompts, golden sets in git, LLM-as-judge
- Cost engineering: prompt cache, semantic cache, model router, batching
- Secure integration: authentication, secret management, audit logging
Tools and frameworks
- Python + TypeScript
- Anthropic SDK · OpenAI SDK · Azure OpenAI · AWS Bedrock
- LangGraph · Pydantic AI · DSPy
- Langfuse · OpenTelemetry
- Model Context Protocol (MCP)
- Docker · Vercel · Railway
Example deliverables
- 01Client-facing agent that reads, decides and acts — with HITL approval
- 02RAG system for enterprise documentation with documented quality
- 03Migration from prototype to production with full operations stack
- 04Cost-optimised LLM pipeline with model router and cache
Track courses
8 kursDisse kursene er unike for Ignite Builder. Felleskursene som alle Ignitere tar finner du på kursoversikten.
- BuilderIn Adopt
User feedback and instrumentation
Build AI systems that learn how they're actually used.
- BuilderIn Build
Production agent patterns
Streaming, retries, circuit breakers — patterns that keep agents alive in production.
- BuilderIn Build
MCP integrations and custom server design
Connect agents to enterprise data and actions through Model Context Protocol.
- BuilderIn Build
Eval CI with golden sets in Git
Regression-test prompts and agents — break the build when quality drops.
- BuilderIn Foundations
Multi-provider stack: Anthropic, Azure, AWS
Why you should speak three dialects of LLM.
- BuilderIn Operate
Semantic cache and prompt-cache strategies
Save 30–80 % of token cost without losing quality.
- BuilderIn Operate
Azure deployment for Norwegian clients
Cloud architecture that satisfies Norwegian data requirements — and that you can defend in a security committee.
- BuilderIn Operate
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Career path after graduation
After graduation you are billable as an AI Engineer at premium rate. You work with clients building agentic platforms, migrating legacy to AI-native workflows, or setting up RAG systems for regulated data.
Who should choose this track
Choose Builder if you love writing code, want to build things more than one person uses, and are curious about both the AI side and the operations side.
Certifications
- Microsoft AI-102 (required)
- AWS AI Practitioner (recommended)
See how the year is structured
Six phases, 42 courses and 10 months. The program builds each profile gradually.