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Data Science & ML

What does a AI Engineer do?

Builds products and internal tools on large language models.

High demand Team: AI / LLM Applications Reports into: Data Science & ML

What they actually do

Chat/agent features, retrieval (RAG), document automation.
Evaluate model quality and safety.
Manage prompts, vector databases, LLM costs.
Often builds "ask your data" natural-language analytics tools.

Hiring demand

High demand. Large, steady volume of postings across industries. A realistic target for an active job search.

Ad space

Who they work with

ProductSoftware engineeringSecurity & legalAnalytics

Typical tools

PythonLLM APIsVector databasesEval frameworks

Skills to get there

Python
Prompt & eval design
Software engineering
Product sense

Title ladder

Common titles for this role at each level. Companies vary; see Role titles decoded.

Level	Typical titles
Entry	Junior / Associate AI Engineer · AI Engineer I
Mid	AI Engineer · AI Engineer II
Senior	Senior AI Engineer · Lead AI Engineer
Expert (IC track)	Staff / Principal AI Engineer
Management track	Manager, AI / LLM Applications → Director of AI / LLM Applications → VP

See the free training path →

See current openings

Searching for: AI Engineer · anywhere in the US · change

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Opens the job board's own search; results and counts are theirs.

How to get here

Salary (US) as of 2026-11

Median$160K

Typical range$110K–$213K

Senior / manager$251K

Sources:

Mapped to BLS 15-1252. 'AI Engineer' titles range from LLM app developers to research engineers; Levels.fyi ML/AI SWE median ($251k) is the senior anchor.

Experience to get here

Entry level1-3 years (software engineering background)

Typical title2-6 years; 4-6 is the most common posted band

Bachelor's in CS or engineering is typical; 28% of postings ask for a PhD and 24% a master's, but LLM-application roles weigh shipped products over degrees.

Typical prior roles

Software Engineer (backend/full-stack)Machine Learning EngineerData ScientistSolutions / Forward-deployed Engineer

Must have

Python (71-83% of postings); TypeScript/React useful for product-facing roles
LLM integration: prompt design, RAG, vector databases, agents (RAG in 36-54% of postings)
Evaluation and safety: building eval sets and monitoring quality
Production engineering: APIs, Docker, CI/CD, cloud (AWS most named)
Product sense: scoping what an LLM feature should and should not do

Milestones people hit first

Shipped a RAG or agent feature to real users with an eval harness
Built a prompt/eval pipeline that caught regressions before release
Reduced LLM cost or latency measurably (caching, routing, smaller models)
Integrated an LLM API into an existing product with security/legal review

Certifications

AWS Certified Machine Learning Engineer - AssociateAmazon Web Services

Nice to havein postings: rarely

Exam fee	$150
Training	AWS Skill Builder free tier
Renewal	recertify by exam every 3 years
Typical total	$150-400

Time: 6-10 weeks part-time
Prerequisites: none

AWS is the most-named cloud in AI engineer postings, but certs are almost never listed as requirements.

Google Cloud Professional Machine Learning EngineerGoogle Cloud

Nice to havein postings: rarely

Exam fee	$200
Training	Google Skills learning path
Renewal	valid 2 years; renew via Google Skills
Typical total	$200-500

Time: 6-10 weeks part-time
Prerequisites: none

Relevant for Vertex AI / Gemini-based stacks; GCP named in only ~4% of AI engineer postings.

Training & learning

DeepLearning.AI short courses: RAG, Agentic AI, Evaluating Agentic Applications, MCP FREE DeepLearning.AI · learning path · short courses free · 1-2 hours each; RAG course ~26 hoursThe fastest route to the exact patterns postings name: RAG, agents, evals, tool use.
Generative AI with Large Language Models FREE AWS / DeepLearning.AI (listed on deeplearning.ai) · course · via Coursera subscription; free to audit · about 13 hoursCovers fine-tuning, RLHF basics and deployment trade-offs that interviews probe.
Deep Learning Specialization DeepLearning.AI on Coursera · course · Coursera subscription ($49/mo or Coursera Plus $239/yr) · about 3 months at 10 hrs/weekTransformers and sequence models underpin LLMs; PyTorch appears in ~22-38% of postings.
What 1,000+ Job Descriptions Reveal About the AI Engineer Role in 2026 FREE AI Shipping Blog (Alexey Grigorev) · community · free · 20 minutesSkill frequencies (Python 82%, RAG 36%, LangChain 19%, Docker 31%) to prioritize your portfolio.
AI Engineer Job Outlook 2026 (903 postings) FREE 365 Data Science · community · free · 20 minutesDegree, experience and salary bands employers actually post for AI engineer roles.

Sources & notes

No certification shows up 'often'; none of the three posting analyses (903, 889 and active-postings samples) report cert frequency, and the roles are evaluated on shipped work. Only two certs listed for that reason. Glassdoor AI Engineer page not available. Prior-role list is inferred from the skill mix (software engineering plus ML), not from a prior-role survey.

Figures are US, from the sources listed, and change often; verify before deciding.

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