Data & AI Engineer

Data & AI Engineer Our client is seeking a pragmatic, hands-on Data & AI Engineer to design, build, and operate AI-powered applications and agents that solve real business problems. You’ll join our client’s team to enhance existing AI solutions, create new AI capabilities that improve workflows and decision-making, and work closely with business stakeholders and engineers to embed domain expertise into robust, production-grade AI systems. Key Skills & Experience Python software development – Strong, production-level coding skills to build reliable, maintainable AI services. End-to-end software delivery – Experience designing, building, testing, deploying, and operating production-grade systems. AI/LLM application development – Hands-on experience creating AI or LLM-based applications used by real users, not just experimenting with consumer tools. AI system lifecycle – Exposure to prototyping, data preparation, evaluation, deployment, monitoring, and continuous improvement of AI systems. AI evaluation and metrics – Ability to design and run evaluations, and measure model/agent quality, reliability, safety, and business impact. Working with multiple model providers – Understanding of different model families, trade-offs in latency, cost, context limits, and deployment constraints. Prompt and agent design – Experience treating prompts and agent instructions as versioned, testable software artifacts. Systems integration – Integrating AI with APIs, enterprise applications, data platforms, and both structured and unstructured data. Advanced AI techniques – Familiarity with retrieval-augmented generation, tool calling, structured outputs, agent orchestration, and workflow automation. Model adaptation foundations – Understanding when to use prompting, retrieval, fine-tuning, and how to prepare and evaluate data and models for post-training. Business and data understanding – Ability to grasp complex workflows, rules, and processes, and translate them into AI-enabled solutions.