@bashifuirkashi: Want to become an AI engineer in 2026? Build these 15 projects to make the upgrade from Software Engineer to AI Engineer: 1️⃣ Model regression detection system CI/CD but for model behavior. 2️⃣ LLM cost autopilot Route every request to the cheapest model that still performs well. 3️⃣ Failure forensics tool for AI pipelines Find exactly which step broke when a multi-step pipeline produces garbage. 4️⃣ Self-healing documentation bot Auto-detect when code changes make your docs stale and generate the fix. 5️⃣ LLM output arbitration system Multiple models critique any LLM response then an adjudicator resolves disagreements. 6️⃣ RAG pipeline with hybrid search Dense vectors + BM25 + reranking + citation verification. 7️⃣ Semantic caching layer Serve cached responses for semantically similar prompts and cut API costs 30–60%. 8️⃣ Text-to-SQL with guardrails Natural language → SQL with hallucination detection and destructive query blocking. 9️⃣ Prompt versioning + A/B testing platform Git for prompts with traffic splitting and statistical significance testing. 🔟 Fine-tuning pipeline with LoRA End-to-end dataset curation → training → eval → deployment with experiment tracking. 1️⃣1️⃣ LLM gateway with rate limiting + fallback routing Per-team budgets, circuit breakers, and automatic provider failover. 1️⃣2️⃣ AI feature flag system Gradual rollout with real-time quality monitoring and auto-rollback. 1️⃣3️⃣ Automated eval dataset generator Turn production logs into a self-growing eval dataset. 1️⃣4️⃣ Multi-modal document processor OCR + LLM extraction + business rule validation + human review queue. 1️⃣5️⃣ Agent orchestration system Multi-agent with tool use, persistent memory, and human-in-the-loop escalation. None of these are “I called an API and deployed a chatbot.” #ai #softwareengineer #Tech #aiengineer #jobmarket #aijobs
