AI Engineer - remote job

Dura Digital is hiring a AI Engineer. The role sits in IT and programming and is fully remote. The company places no restriction on where the candidate lives, so you can apply from anywhere.

The employer did not publish a figure; that is settled at interview. The advert sets no condition on working hours.

This vacancy passed an automated check: the list excludes any advert requiring a foreign work permit, visa sponsorship, a particular citizenship, or residence in a specific country.

A 2-3 sentence summary of the role: Dura Digital is seeking an AI Engineer to design, build, and deploy AI-powered solutions that enhance operational efficiency and customer experiences. You will work closely with cross-functional teams to turn ambiguous business needs into practical, production-ready systems.

What you will do: - Build and deploy production AI features, including LLM-backed workflows, retrieval-augmented generation, and traditional ML models. - Own the data path, from ingestion to retrieval quality, and continuously improve it based on measured outcomes. - Design and implement evaluation frameworks to ensure system quality and track regressions. - Integrate AI capabilities into existing applications through well-designed APIs, focusing on performance and reliability. - Monitor deployed systems for quality drift, hallucination rates, and token spend, and take corrective actions. - Apply responsible-AI practices, including data privacy and handling sensitive information. - Quickly prototype solutions to reduce uncertainty and make deliberate decisions on which features to harden. - Contribute to internal standards and reusable components for other teams. - Communicate technical tradeoffs to non-technical stakeholders, ensuring clear and honest explanations.

What they are looking for: - 3+ years of professional software engineering experience, with 1+ years in production AI systems. - Strong Python skills, and proficiency in at least one of TypeScript/JavaScript, C#, Java, or Go. - Experience shipping an AI feature end to end, including problem framing, evaluation, and post-deployment support. - Practical knowledge of modern LLM toolkits, prompt design, and structured output. - Experience with retrieval systems and vector search technologies. - Cloud deployment experience on Azure, AWS, or GCP, including containers, CI/CD, and infrastructure-as-code. - Data engineering skills, including SQL and building robust data pipelines. - Clear communication and comfort operating with incomplete requirements.