AI Engineer

We are looking for a technically strong Engineer to lead the development and operationalization of advanced AI-driven solutions. This individual will combine solid software engineering fundamentals with applied generative AI expertise to deliver scalable, real-world systems.In this role, you'll architect and deploy distributed AI solutions designed to improve service delivery workflows and support high-accuracy documentation standards. The ideal candidate thrives in production environments and understands how to translate experimental AI capabilities into secure, reliable applications.Key ResponsibilitiesAI System Design & OperationalizationArchitect, build, and maintain AI-enabled applications leveraging large language models, retrieval-based architectures, and modern ML lifecycle practices. Ensure systems are production-ready, observable, scalable, and resilient.Distributed Agent SystemsDevelop coordinated multi-agent architectures capable of managing complex workflows, maintaining context, and orchestrating interactions across services to automate operational processes.Platform & Backend EngineeringDesign and implement cloud-native backend systems using scalable design patterns such as event-driven services, serverless components, containerized workloads, managed databases, and object storage. Integrate solutions with existing enterprise platforms and structured data systems.Security & Data GovernanceEmbed secure development practices across the AI lifecycle. Ensure systems follow responsible AI, data protection, and secure architecture principles.Model Optimization & Lifecycle ManagementImplement structured prompt strategies, performance evaluation frameworks, monitoring systems, and version control for prompts and models. Drive continuous iteration and improvement across deployed AI systems.Cross-Functional DeliveryPartner closely with product stakeholders and engineering teams to convert operational needs into scalable technical solutions within an Agile development framework.Required Background • Professional Experience: Minimum 3 years of software engineering experience with strong proficiency in Python and hands-on deployment of production systems. • AI/ML Deployment: Demonstrated experience shipping and supporting AI or ML applications in live environments, including model hosting, monitoring, and lifecycle governance. Exposure to AWS, Azure, GCP, or equivalent infrastructure required. • Engineering Foundations: Solid understanding of the software development lifecycle, REST APIs, microservices architecture, containerization (Docker, Kubernetes), and CI/CD practices supporting ML workflows. • Generative AI & LLM Expertise: Experience working with large language models, embeddings, vector search technologies, retrieval pipelines, and distributed agent design concepts. Familiarity with orchestration frameworks and agent coordination strategies.Preferred Experience • Exposure to regulated data environments and secure information handling standards. • Background in NLP applications involving structured or unstructured documentation workflows. • Experience with MLOps tooling such as experiment tracking systems, model registries, feature management platforms, and AI observability solutions. • Familiarity with agent orchestration frameworks and multi-agent workflow tooling. The Phoenix Group Advisors is an equal opportunity employer. We are committed to creating a diverse and inclusive workplace and prohibit discrimination and harassment of any kind based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We strive to attract talented individuals from all backgrounds and provide equal employment opportunities to all employees and applicants for employment.