NET AI Developer

Architect & Build: Lead the design and implementation of highly scalable, resilient, and event-driven applications utilizing .NET, enterprise messaging platforms, and cloud-native architecture patterns.

Modernize: Champion system modernization by transitioning legacy applications toward distributed .NET services, cloud-native platforms, and modern data stores to support reliable transaction processing.

Leverage AI: Utilize Generative AI coding assistants to accelerate development workflows-including implementation, refactoring, unit testing, code reviews, automation, and troubleshooting-while maintaining strict ownership of code quality.

Optimize Workflows: Implement agentic workflows, spec-driven development, custom instructions, and prompt engineering to enhance developer productivity and team execution.

Drive Quality: Ensure engineering excellence through automated testing, rigorous code reviews, performance analysis, observability, and production readiness practices.

Collaborate & Mentor: Partner closely with architects, product owners, and adjacent technology teams to translate business requirements into high-quality technical solutions. Guide and mentor engineers to establish repeatable practices for effective and responsible AI-assisted development.

Bachelor’s degree in Computer Science, Software Engineering, a related technical field, or equivalent practical experience.

7 years of professional software engineering experience developing highly available, scalable .NET, cloud-based, and web service applications for high-volume transactions.

6 years of experience building and deploying cloud-native applications utilizing modern cloud platforms (e.g., Google Cloud Platform, AWS, or similar environments), Docker, Kubernetes, microservices, and CI/CD pipelines.

2 years of experience working with modern databases (e.g., MongoDB, PostgreSQL, Aerospike, or comparable relational and NoSQL platforms).

2 years of experience in system modernization initiatives, transitioning legacy platforms to distributed .NET applications and modern data architectures.

2 years of hands-on experience with AI/ML implementations, AI-assisted engineering practices, and Large Language Models (LLMs).

Demonstrated technical leadership experience in designing event-driven architectures using streaming and messaging platforms (e.g., Kafka, enterprise message queues).

Hands-on experience utilizing Generative AI coding assistants (e.g., GitHub Copilot) across SDLC workflows and IDE/CLI environments.

Working knowledge of agentic workflows, custom instructions, and prompt engineering.

Experience operating in an Agile environment and utilizing Agile project management tools.

Preferred qualifications:

Master’s degree in Information Technology, Computer Science, Artificial Intelligence, Software Engineering, or a related field.

Deep understanding of enterprise financial operations, transaction processing, and highly regulated domain capabilities.

Experience with Test-Driven Development (TDD), Behavior-Driven Development (BDD), and enterprise QA automation.

Strong background in performance engineering, reliability testing, observability patterns (e.g., Splunk), and the Twelve-Factor App methodology.

Proficiency in generating comprehensive architecture diagrams, technical specifications, and production runbooks.

Prior exposure to leading AI-assisted SDLC transformation initiatives and enterprise developer productivity programs.

Excellent communication skills with a proven track record of mentoring engineers on .NET practices, distributed systems, and responsible AI software delivery.

As a Senior .NET AI Developer at a leading enterprise financial institution, you will spearhead AI-integrated workflows across the System Development Life Cycle (SDLC). You will operate at the cutting-edge intersection of .NET engineering, event-driven architecture, cloud-native platforms, and Generative AI-assisted delivery. Your mission is to architect and build intelligent, resilient business solutions tailored for complex, high-volume financial environments. Bringing a collaborative mindset and a bias for action, you will partner with cross-functional teams to drive outcomes and shape the future of AI-assisted engineering within the organization.