• Design, develop, and maintain scalable, multitenant SaaS applications using .NET 6+ and microservices-based distributed architectures. • Support, maintain, and modernize legacy .NET Framework 4.7.2 monolithic applications while planning and executing migration strategies. • Build high-performance, secure, and well-documented RESTful APIs and integrations with third-party APIs. • Apply industry-standard architecture patterns, best practices, and clean code principles to ensure maintainability and scalability. • Collaborate with the Technical Lead and Architect to ensure alignment with architectural direction, coding standards, and system design goals. • Work closely in a fully remote, cross-functional Agile team to deliver business-critical software solutions. • Write and maintain unit tests to ensure software quality and reliability. • Own the end-to-end delivery of significant features or projects, including technical design, implementation, and deployment. • Troubleshoot, debug, and optimize application performance in production and staging environments. • Participate in Agile ceremonies (backlog refinement, sprint planning, standups, retrospectives, demos) and act as a technical lead when needed. • Mentor and coach less senior engineers, fostering technical excellence and knowledge sharing across the team. • Contribute to continuous improvement of development processes, tooling, and deployment pipelines. • Other relevant projects as needed or assigned

• Design, develop, and maintain end-to-end GenAI-powered applications. • Build responsive, user-friendly UIs using modern JavaScript frameworks. • Develop scalable backend services and APIs using Python and FastAPI. • Implement AI workflows and orchestration. • Collaborate with product, design, and AI teams to translate requirements into high-quality solutions. • Deploy, monitor, and optimize applications in cloud environments. • Ensure performance, security, and scalability best practices are followed.

• Design and manage the development of scalable generative AI systems and enterprise-grade AI platforms. • Create robust architectures that facilitate model training, inference, monitoring, and lifecycle management within production settings. • Lead the choice, customization, and enhancement of cutting-edge generative AI and large language models. • Develop and implement APIs, microservices, and integration frameworks to integrate AI functionalities into enterprise applications. • Ensure that AI platforms adhere to high benchmarks for performance, reliability, security, and scalability, while also complying with data governance and privacy standards. • Work collaboratively with product, engineering, and business teams to define technical requirements and AI architecture approaches. • Design end-to-end pipelines for the deployment and monitoring of AI models, ensuring smooth integration with existing systems. • Lead architectural choices for LLM applications, AI workflows, and distributed AI infrastructure. • Establish best practices for responsible AI development, including protocols to address risks such as model hallucinations, bias, and reliability issues. • Offer technical guidance and mentorship to engineering teams while assisting in shaping long-term technology strategy and the evolution of AI platforms.

• Collaborate with a diverse group of individuals • Propose product and technical changes • Deliver best-in-class software • Participate in code reviews • Grow skills and career through onboarding and mentorship • Own and deliver stories with peer consultation • Integrate and use monitoring and alerting tools