Genesys is seeking a Senior AI Application Developer to design and deliver enterprise-grade AI applications that address complex business challenges across multiple domains, contributing to their AI Services platform by establishing best practices and reusable components, while focusing on secure, scalable, and compliant enterprise AI solutions.
Requirements
- 5+ years of enterprise software development experience, including at least 2+ years working with AI/ML applications.
- Strong proficiency in Python, Java, and/or JavaScript/TypeScript.
- Proven experience deploying AI/ML models into production systems at enterprise scale.
- Familiarity with cloud platforms such as AWS, Azure, or GCP, and container orchestration tools like Kubernetes and Docker.
- Experience with distributed systems integration patterns including APIs, microservices, and messaging systems.
- Experience with LLM-based application frameworks such as LangChain, Semantic Kernel, or Haystack.
- Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG).
Responsibilities
- Lead the design, development, and deployment of AI-driven applications for enterprise use cases such as customer engagement, workflow automation, and decision support.
- Build applications that integrate seamlessly with the AI services platform to ensure reusability and alignment with enterprise standards.
- Translate business requirements into scalable AI-enabled solutions, balancing innovation with operational excellence.
- Contribute production-ready modules, APIs, and integration patterns to the shared AI services framework.
- Partner with platform and architecture teams to ensure scalability, observability, multi-tenancy, and compliance.
- Identify and resolve platform gaps surfaced through real-world application needs.
- Ensure applications meet enterprise security, compliance, and governance standards, including data privacy, auditability, and responsible AI practices.
Other
- Bachelor’s degree in Computer Science, Software Engineering, or related field (Master’s preferred).
- Collaborate with data scientists, engineers, architects, and business stakeholders to translate cutting-edge AI capabilities into reliable production-ready applications.
- Advocate for responsible AI practices, including explainability, bias mitigation, and safe model use.
- Collaborate with data scientists and ML engineers to operationalize models at scale.
- Work closely with enterprise architects to align with IT and business strategies.
