AI engineer
In plain wordsA software developer who builds products using ready-made AI models — connecting them to data and tools and testing that they work well — rather than inventing or training the models.
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Foundation-model eraemerging
A software engineer who specializes in building products and features on foundation modelsfoundation model, n.: A very large AI model, built once at great cost from vast amounts of text, images or code gathered mostly from the internet, that many products then reuse as their starting point, from chatbots to coding tools., practicing AI engineeringAI engineering, n.: The craft of building useful, reliable products on top of AI models — choosing models, writing prompts, connecting data and tools, testing quality and running it all safely at scale.: integrating model APIsmodel API, n.: A web service through which programs send requests to an AI model run by a company and receive its answers, usually paying per use instead of running the model themselves. and open-weight models, designing prompts and context, building retrievalretrieval-augmented generation, n.: Giving an AI an open-book exam: before answering, it looks up relevant passages in a set of documents and bases its reply on them, often citing where each point came from. pipelines, agents and tool integrations, writing evaluations, and shipping and monitoring the result. The role sits on the application side of what its popularizer called the 'API line': it calls for product sense and software skill more than research training, in contrast with the machine learning engineermachine learning engineer, n.: An engineer who turns machine-learning ideas into working systems: preparing data, training and testing models, and running them reliably inside real products., who trains and deploys models, and the research scientist or research engineer, who develops new ones. Job postings with the title grew rapidly from 2023, though responsibilities vary widely between employers.
We hired an AI engineer to build the support agent; none of us had trained a model, and we didn't need to.
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General
Loosely, any engineer who works on artificial-intelligence systems, including those who collect data and who train, optimize and deploy models; an older, generic job title used across industry and in public-sector workforce plans before the specialized application-building sense emerged in 2023.
Origin
A generic title for years; the specialized sense was popularized by Shawn 'swyx' Wang's essay 'The Rise of the AI Engineer' (Latent Space, 30 June 2023), which predicted it would become the highest-demand engineering job of the decade and noted that machine-learning-engineer postings then outnumbered AI-engineer postings about ten to one.
Related
- AI engineeringAI engineering, n.: The craft of building useful, reliable products on top of AI models — choosing models, writing prompts, connecting data and tools, testing quality and running it all safely at scale.
- machine learning engineermachine learning engineer, n.: An engineer who turns machine-learning ideas into working systems: preparing data, training and testing models, and running them reliably inside real products.
- prompt engineerprompt engineer, n.: A person whose job is writing and testing the instructions given to AI models so they behave reliably; hyped in 2023 as a six-figure job anyone could learn, the role has since largely merged into ordinary engineering.
- LLMOpsLLMOps, n.: The everyday work of running chatbots and other products built on large language models: tracking prompts, testing answers, watching cost and quality, and updating safely when models change.
- Software 3.0Software 3.0, n.: Andrej Karpathy's name for programming computers by writing plain-language instructions for AI models, following traditional code (Software 1.0) and trained neural networks (Software 2.0).
- data sciencedata science, n.: The practice of collecting, cleaning, analyzing and interpreting data, using statistics, programming and machine learning, to answer questions and guide decisions.
- machine learning engineermachine learning engineer, n.: An engineer who turns machine-learning ideas into working systems: preparing data, training and testing models, and running them reliably inside real products.
Sources
- Wang, S. (2023). The Rise of the AI Engineer. Latent Space, 30 June 2023. latent.space/p/ai-engineer
Mentioned in
AI engineeringAI engineering, n.: The craft of building useful, reliable products on top of AI models — choosing models, writing prompts, connecting data and tools, testing quality and running it all safely at scale., machine learning engineermachine learning engineer, n.: An engineer who turns machine-learning ideas into working systems: preparing data, training and testing models, and running them reliably inside real products., forward deployed engineerforward deployed engineer, n.: An engineer from an AI or software company who works directly inside a customer's organization, building and tailoring the company's systems to that customer's real problems.