Roles That Are Growing
Ml Eng
You're in the growth zone. MLOps, LLM ops, RAG — all hiring.
Data Eng
Data pipelines feed AI. Your skills are the foundation. Demand is up.
Platform
AI infra: vector DBs, model serving, cost control. Platform engineers are in high demand.
Roles That Are Growing
TL;DR
- Indeed: AI-related postings surged 130% YoY. Tech with AI mentions: 45% above Feb 2020. Total tech: 34% below. Data & analytics leads at 45% AI mention share.
- AI Product Engineer, MLOps, Data Engineer, Platform Engineer—all growing. "AI" in the title isn't required. "Feeds AI" or "builds AI infra" counts.
- AI created 1.3M new roles in two years (WEF). Workers with AI skills earn up to 56% more (IMF/OECD). Differentiate.
More demand doesn't mean "sit back and get hired." It means opportunities exist if you're prepared. The gap between AI-mentioning jobs and everything else is stark. Get on the right side.
Roles With Increased Demand (2024–2026)
| Role / Title | Why | Sector Signal |
|---|---|---|
| AI Product Engineer / AI Engineer | Companies need people who ship AI features. New role, fast growth. | Software dev: 20%+ AI share |
| MLOps / ML Engineer | Model deployment, LLM ops, RAG pipelines. AI in production needs this. | Scientific R&D: 20%+ |
| Data Engineer | Pipelines feed RAG and embeddings. Data quality = AI quality. | Data & analytics: 45% (highest) |
| Platform Engineer | Vector DBs, model APIs, cost and latency. AI infra is platform work. | IT systems: 20%+ |
| Solutions Architect (AI) | Enterprises need "how do we add AI?" guidance. Consulting and pre-sales. | Marketing: 14.9%, HR: 8.8% |
| DevRel / Technical Evangelist (AI) | Frameworks need advocates. LangChain, LlamaIndex ecosystem is hiring. | — |
| Security (AI/ML) | Model security, prompt injection, data leakage. New specialty. | — |
Indeed Hiring Lab (Dec 2025): Data & analytics leads AI mention share. Software, IT, R&D close behind. Marketing doubled in 2025. HR doubled. These aren't niche anymore.
The "AI-Adjacent" Play
You don't need "AI" in your title. "Backend Engineer — AI/ML team" or "Data Engineer — RAG pipelines" works. The work touches AI. That's the signal.
Caveats
- Growth ≠ stability. These roles are hot. They can cool. Build transferable skills.
- Geography matters. Remote has expanded, but some roles are location-heavy (e.g., defense, on-site).
- Level matters. Senior+ growth is stronger than junior. Companies want people who can lead.
How to Verify Demand Yourself
Don't take our word for it. Go to LinkedIn Jobs, Indeed, or Levels.fyi. Search "AI Product Engineer," "MLOps," "Data Engineer." Filter by "posted in last 30 days." Count. Compare to a role you know. The delta tells you something.
Same for your city or remote preference. Some roles cluster in certain regions. AI roles tend to be more remote-friendly than traditional infra roles. Check.
2022: 'Backend Engineer' or 'Data Engineer.' AI was a niche. Few roles mentioned it.
Click "Growth roles now" to see the difference →
Quick Check
You're a backend engineer. How can you tap into growing AI demand without changing your title?
Do This Next
- Pick one growing role that fits your background. Data Engineer, MLOps, AI Product Engineer—what's your closest match?
- Indeed + LinkedIn search — Filter "posted last 30 days." Count AI-mentioning vs non-AI for your role. See the gap.
- Identify the skill add — One project (RAG pipeline, cost dashboard, prompt ops) that bridges you. Build it and document it.