• Develop and maintain backend services using .NET / C#. • Build REST APIs and backend endpoints following best practices. • Design and implement database solutions using SQL Server / PostgreSQL / MySQL. • Write efficient queries, optimize performance, and ensure data integrity. • Integrate backend services with external systems using APIs and webhooks. • Implement authentication/authorization (e.g., JWT, OAuth2) and security best practices. • Create and maintain background jobs/queues using technologies like Hangfire / Quartz / Azure Functions / Service Bus (as applicable). • Build and maintain microservices or modular monolith architecture (as per project needs). • Work with caching mechanisms (e.g., Redis) if required. • Perform code reviews, debugging, and ensure high-quality code and documentation. • Use Git workflows and follow agile/Scrum practices. • Support production deployments and resolve issues in a timely manner.

• Build and ship **robust backend services **and** frontends** with real product impact • Ensure systems are scalable, performant and easy to maintain • Collaborate across teams to integrate services and deliver end-to-end value • Model business domains into clean, performant data structures • Coach and mentor other engineers on best practices to help them grow • Collaborate with other engineers and lead technical delivery on initiatives within a domain or project • Lead by example in engineering excellence, pragmatism and shared ownership.

• Develop, maintain, and troubleshoot applications using C# and the .NET platform. • Write clean, maintainable, and well-documented code. • Collaborate with senior developers, QA engineers, and other team members to deliver high-quality software. • Participate in code reviews and implement feedback. • Debug and resolve software defects and performance issues. • Follow established coding standards and development best practices.

• Architect & Build: Design and deliver agentic workflows and scalable microservices, primarily using Python, within a distributed system architecture. • AI Integration: Lead the integration of Generative AI capabilities, including LLM APIs, RAG pipelines, and agentic workflows into our production systems. • Agentic Operations & Observability: Implement operational practices, observability, and autonomous monitors (e.g., detecting intelligence drift or hallucinations) to ensure AI reliability in production. • Elevate Engineering: Drive overall engineering quality and speed by implementing AI-SDLC practices, ensuring high standards through rigorous code reviews, test automation, and by establishing continuous, trace-based quality evaluation for all software and agentic components. • Mentor & Innovate: Evaluate emerging AI tooling, mentor fellow engineers, and contribute directly to our technical roadmap and Agentic AI-SDLC and Production Operations.