Senior AI Engineer – Generative AI, Agentic Systems

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🔥 0 minutes ago

🇦🇪 United Arab Emirates (UAE) – Remote

⏳ Contract/Temporary

🟠 Senior

🗣️ LLM Engineer

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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datavent.io

WebsiteLinkedInAll Job Openings

2 - 10 employees

Founded 2024

🤝 B2B

🤖 Artificial Intelligence

💼 Consulting

B2B • Artificial Intelligence • Consulting

datavent. io is a B2B data engineering and platform consulting firm that builds cloud-native, AI-ready data platforms and lakehouse architectures for analytics and production AI. They deliver end-to-end services — architecture, ingestion, transformation, modeling, MLOps/RAG pipelines, vector stores/feature stores, and ongoing platform stewardship — on customers' clouds and stacks (AWS, GCP, Azure, Snowflake, Databricks or on-prem) with a no-vendor-lock-in approach. The company emphasizes production outcomes (ship production pipelines, not prototypes), rapid delivery, and integrations across many data sources for enterprises in industries like banking, telecom, manufacturing and B2B SaaS.

📋 Description

• Design and implement Python services connecting large language models to enterprise APIs, data sources and approved tools • Build retrieval-augmented generation systems, including document ingestion, indexing, retrieval, reranking and source attribution • Engineer agentic workflows with explicit permissions, reliable state handling, retries, audit trails and approval gates for consequential actions • Develop document intelligence pipelines producing validated structured outputs for downstream applications and ERP workflows • Create evaluation datasets and release criteria • Measure answer quality, failure modes, latency and operating cost • Deploy and operate AI applications in customer-controlled cloud or private environments • Monitor systems, handle incidents and provide clear handover documentation • Work closely with founders and customer engineering teams • Own meaningful technical decisions and shape enterprise AI engineering practices

🎯 Requirements

• A record of delivering production software and LLM applications, with responsibility for architecture, deployment and operational quality • Strong Python, API design, testing and debugging • Practical experience with containers, Git and CI/CD • Hands-on experience with RAG, tool use, structured outputs and evaluation beyond prompt experimentation • Experience with Amazon Bedrock, Anthropic Claude or comparable model services • Judgement to select models and deployment patterns for a use case • Ability to assess data access, untrusted inputs and agent permissions • Ability to explain trade-offs to customers and guide engineering decisions in English • Experience with self-hosted models, GPU infrastructure, vector search, MCP integrations or agent frameworks is valuable • CV, location and availability required in application • Production AI example covering contribution, evaluation approach, deployment environment and an addressed failure mode required in application • Applications must be submitted through the job portal

🏖️ Benefits

• 3-month contract • 3-month probation period • 1 day of annual leave • Opportunity to work closely with the founders • Ownership of meaningful technical decisions • Opportunity to shape how the team builds, evaluates and operates enterprise AI • Collaboration with customer engineering teams

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