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From 51 similar postings that came down. Coming down is not always a hire.
Senior Data Scientist
Reads like an AI Engineer role: building products on existing AI models.
Location not stated
Actively hiring, first seen by us 2 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingBuild autonomous agentic systems for multi-step reasoning, planning, and tool use
Take models and agents from prototype through production deployment
Build and maintain LLM evaluation tooling for performance and reliability
Build LLM apps for natural-language querying of structured and tabular data
Implement and optimize RAG pipelines to ground agent outputs in verifiable data
From the employer’s posting
Design, build, and iterate on autonomous agentic systems capable of multi-step reasoning, planning, tool use, and self-correction
Contribute to end-to-end model and agent development, from prototyping through production deployment
Develop and maintain LLM evaluation tooling to track model performance, reliability, and consistency
Build LLM-powered applications over structured and tabular data, enabling natural-language querying, analysis, and insight generation on enterprise datasets
Implement and optimize Retrieval-Augmented Generation (RAG) pipelines to ground agent outputs in real, verifiable data sources
What you’ll bring
All qualificationsCore experience
- 10+ years of experience in data science or related work
- Experience with LLMs, agents, and RAG pipelines
- Ability to communicate technical concepts to technical and non-technical audiences
Qualification wording
We are looking for a NLP / AI Data Scientist with 10+ years of experience
Implement and optimize Retrieval-Augmented Generation (RAG) pipelines
Communicate technical concepts to both technical and non-technical audiences
Posting record
Report an errorActively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 11, 20262 days ago
- Recorded sightings
- 3
- Last seen by us
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
krb-sjobs:25008:5012 is hiring
18 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description
Your Role
Are you passionate about directly impacting the business by utilizing analytical and machine learning skills? Do you want to play a key role in designing and building autonomous AI agents, mining large datasets, developing advanced statistical and language models to generate meaningful and actionable insights, improve decision-making, optimize business processes, and help address business problems?
We are looking for a NLP / AI Data Scientist with 10+ years of experience:
• Contribute to end-to-end model and agent development, from prototyping through production deployment, adhering to best practices for software engineering and reproducible research
• Design, build, and iterate on autonomous agentic systems capable of multi-step reasoning, planning, tool use, and self-correction
• Develop and maintain LLM evaluation tooling to track model performance, reliability, and consistency across a variety of metrics throughout the development and deployment lifecycle
• Build LLM-powered applications over structured and tabular data, enabling natural-language querying, analysis, and insight generation on enterprise datasets
• Implement and optimize Retrieval-Augmented Generation (RAG) pipelines to ground agent outputs in real, verifiable data sources
• Work closely with data engineering and platform teams to ensure reliable, scalable, and production-ready data pipelines for AI systems
• Communicate technical concepts to both technical and non-technical audiences
Are you passionate about directly impacting the business by utilizing analytical and machine learning skills? Do you want to play a key role in designing and building autonomous AI agents, mining large datasets, developing advanced statistical and language models to generate meaningful and actionable insights, improve decision-making, optimize business processes, and help address business problems?
We are looking for a NLP / AI Data Scientist with 10+ years of experience:
• Contribute to end-to-end model and agent development, from prototyping through production deployment, adhering to best practices for software engineering and reproducible research
• Design, build, and iterate on autonomous agentic systems capable of multi-step reasoning, planning, tool use, and self-correction
• Develop and maintain LLM evaluation tooling to track model performance, reliability, and consistency across a variety of metrics throughout the development and deployment lifecycle
• Build LLM-powered applications over structured and tabular data, enabling natural-language querying, analysis, and insight generation on enterprise datasets
• Implement and optimize Retrieval-Augmented Generation (RAG) pipelines to ground agent outputs in real, verifiable data sources
• Work closely with data engineering and platform teams to ensure reliable, scalable, and production-ready data pipelines for AI systems
• Communicate technical concepts to both technical and non-technical audiences
Source details
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