Time since we first saw it
Day 12
Similar jobs usually come down between day 4 and day 77.
From 51 similar postings that came down. Coming down is not always a hire.
Reads like an AI Engineer role: building products on existing AI models.
Work setup in the employer’s posting: TELECOMMUTEFrom the employer’s posting
Design and implement AI workflows combining models, prompts, data and business logic
Build and maintain production-grade AI deployment pipelines
Apply guardrails for safe, explainable and compliant AI behavior
Implement monitoring and observability for usage, performance and drift
Develop and maintain prompt engineering strategies with versioning and testing
Design and implement AI workflows combining models, prompts, enterprise data, tools and business logic
Build and maintain production-grade AI deployment pipelines
Apply guardrails to ensure safe, explainable and compliant AI behavior
Implement monitoring and observability for AI systems, including usage, performance and drift
Develop and maintain prompt engineering strategies, including versioning, testing and optimization
3+ years of experience in data engineering or AI engineering roles
Advanced programming skills in Python
Strong knowledge of MLOps practices and tools
Hands-on experience with Gen AI solutions development and prompt engineering
Solid understanding of SQL and data manipulation techniques
Actively hiringFirst seen by us 12 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 12
Similar jobs usually come down between day 4 and day 77.
From 51 similar postings that came down. Coming down is not always a hire.
673 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
We are looking for a Senior Data Engineer with AI expertise to join our driven team. You will work on an exciting project with our client from the insurance sector, focusing on bridging the gap between data science experimentation and enterprise-grade production systems. The role involves transforming AI models and experiments into scalable, reliable and well-governed solutions that integrate seamlessly into business workflows. You will collaborate closely with data scientists, actuaries and business stakeholders to ensure AI solutions are robust, observable and aligned with governance, reliability and cost-efficiency requirements. Responsibilities Design and implement AI workflows combining models, prompts, enterprise data, tools and business logic Develop and maintain prompt engineering strategies, including versioning, testing and optimization Implement orchestration layers for multi-step reasoning, decisioning and action execution Integrate AI capabilities into enterprise systems, APIs and user interfaces Apply guardrails to ensure safe, explainable and compliant AI behavior Build and maintain production-grade AI deployment pipelines Ensure reliability, scalability, latency optimization and cost efficiency of AI services Implement monitoring and observability for AI systems, including usage, performance and drift Establish change control, versioning, rollback and release management practices Collaborate with data scientists and business experts to validate model behavior and outputs Requirements 3+ years of experience in data engineering or AI engineering roles Strong knowledge of MLOps practices and tools Proficiency in Machine Learning concepts and model lifecycle management Advanced programming skills in Python Hands-on experience with Gen AI solutions development and prompt engineering Solid understanding of SQL and data manipulation techniques Experience integrating AI capabilities into enterprise systems and APIs Familiarity with monitoring, observability and governance for AI systems Ability to work in large enterprise data ecosystems Strong problem-solving and communication skills Proficient communication skills in English (B2 level or higher) Nice to have Knowledge of AI governance and data quality Experience with Apache Spark, PySpark and big data tools Familiarity with Natural Language Processing and LLMs Understanding of retrieval-augmented generation techniques Exposure to (Re)Insurance IT or Palantir platform
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Yes. We’ve followed 7 other Senior Data Engineer, AI jobs there since November 2026. All 7 are still up.
Large employers often post one title for several teams, so these can be separate openings.
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.
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.
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