AI Engineer (US Shared Services)

About the role

Designs, develops, evaluates, and deploys AI-enabled solutions that improve business and operational processes. Applies machine learning, generative AI, large language models, retrieval-augmented generation, and automation to structured and unstructured enterprise data. Integrates models and AI services into secure, reliable production applications and workflows. Establishes testing, monitoring, guardrails, and performance practices to support accuracy, scalability, privacy, responsible use, and measurable business value.

Key responsibilities

• Design, build, evaluate, and deploy AI and machine learning solutions, including generative AI, retrieval-augmented generation, intelligent assistants/agents, predictive models, and workflow automation.
• Integrate foundation models, AI services, APIs, enterprise data sources, and applications to deliver production-ready capabilities.
• Develop evaluation, testing, monitoring, and guardrail practices for model quality, security, privacy, reliability, latency, and cost.
• Partner with product, data, application, and business stakeholders to translate use cases into AI solutions and support adoption.
• Document architectures, reusable components, and MLOps/LLMOps practices to enable maintainable and scalable AI solutions.

About you

• Bachelor's degree in Computer Science, Data Science, Engineering, or related field; equivalent relevant experience may be considered.
• Can work in a Hybrid environment an in a Night-shift schedule
• Experience in artificial intelligence, machine learning, software engineering, or related disciplines, including experience developing or deploying production AI solutions.
• Knowledge of machine learning, generative AI and large language models, retrieval-augmented generation, prompt/context engineering, model evaluation, responsible AI, and cloud-based AI architectures.
• Proficiency in Python and SQL; experience with APIs, cloud AI/ML services, source control, and CI/CD practices.
• Experience with vector search/databases, model or orchestration frameworks, and monitoring/evaluation tools preferred.
• Strong analytical, problem-solving, documentation, and communication skills; ability to work effectively across technical and business teams.