Senior .NET Developer

Overview

Aquent is partnering with a leading financial services institution, a pioneer in delivering innovative and secure solutions, to find exceptional talent. This organization is at the forefront of leveraging cutting-edge technology to redefine the financial landscape, focusing on robust, scalable, and intelligent platforms that serve millions. By joining this team, you will directly contribute to shaping the future of financial services, impacting critical business operations and enhancing user experiences through advanced engineering and AI-driven solutions.

About the Role: Drive Innovation as a Senior .NET Developer with AI Expertise

Are you a passionate and experienced .NET Developer with a strong background in AI, ready to make a significant impact? We are seeking a dynamic individual to join a forward-thinking team that is revolutionizing the System Development Life Cycle through AI-assisted workflows. In this pivotal role, you will be instrumental in building reliable, high-volume business solutions within a complex financial domain, leveraging your expertise in .NET engineering, event-driven architecture, cloud-native platforms, and Generative AI-assisted delivery. This is an incredible opportunity to influence product direction, mentor peers, and contribute to a culture of innovation, directly shaping how technology powers financial success.

What You’ll Do: Your Impactful Contributions

• Contribute to the design and implementation of scalable, resilient, and event-driven applications utilizing .NET, Kafka, and cloud-native architecture patterns.
• Build and modernize high-volume services, APIs, and distributed application capabilities essential for reliable transaction processing and business-critical workflows.
• Collaborate closely with architects, product owners, developers, and adjacent technology teams to translate business capabilities into high-quality technical solutions.
• Leverage Generative AI coding assistants to accelerate implementation, refactoring, unit testing, regression support, code reviews, scripting, automation, troubleshooting, and documentation, while maintaining ownership for correctness and quality.
• Utilize agentic workflows, prompt engineering, custom instructions, and spec-driven development practices to enhance individual and team productivity.
• Elevate engineering quality through automated testing, disciplined code reviews, performance analysis, observability, resiliency practices, and production readiness.
• Support modernization initiatives by transitioning legacy capabilities towards distributed .NET services, cloud-native platforms, event-driven architecture, and modern data stores.
• Collaborate effectively with engineers in a team-oriented environment, fostering the adoption of repeatable and responsible AI-assisted development practices.

What You’ll Bring: Essential Skills & Experience

• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.
• 5+ years of professional software engineering experience developing scalable .NET, cloud-based, or web services applications that support high-volume transactions in highly available environments.
• Hands-on experience designing and implementing scalable, resilient, and event-driven applications using .NET and Kafka, coupled with knowledge of distributed systems, stream processing, performance optimization, and cloud-native architectures.
• Working experience with IBM MQ, Kafka, Splunk, JSON/XML, caching, performance analysis and profiling, Twelve-Factor App methodology, resiliency patterns, and observability patterns.
• Proven experience owning technical components or features and collaborating effectively within a software delivery team.
• 4+ years of experience building and deploying cloud-native applications using GCP, Docker, Kubernetes, microservices, and CI/CD practices.
• Experience with cloud platforms and deployment environments such as PCF, AWS, or GCP.
• 2+ years of experience working with databases such as MongoDB, Aerospike, PostgreSQL, or comparable relational and NoSQL platforms.
• Experience contributing to IT transformation or system modernization initiatives involving legacy platforms, distributed .NET applications, or modern data platforms.
• 1+ years of hands-on experience with AI/ML implementation, production deployment, or AI-assisted engineering practices.
• Hands-on experience or practical exposure to Large Language Models such as GPT, Claude, Gemini, PaLM, or comparable enterprise AI platforms.
• Demonstrated hands-on experience using GenAI coding assistants across SDLC workflows, including implementation, refactoring, unit testing, regression support, code reviews, scripting, automation, troubleshooting, and documentation.
• Practical familiarity with tools such as GitHub Copilot and/or Claude Code in IDE or CLI-based workflows, with the ability to apply AI assistance to reduce context switching and accelerate delivery beyond code generation.
• Working knowledge of agentic workflows, spec-driven development, custom instructions, and prompt engineering, with the ability to apply effective AI-assisted development practices.
• Knowledge of Agile methodology and experience in an Agile working environment.
• Experience with the Atlassian tool stack, including Jira and Confluence.
• A strong understanding of broker-dealer domain capabilities and operations, with preferred experience in the financial services industry.
• Excellent communication skills, with a proven ability to collaborate effectively with engineers and cross-functional partners in a team-oriented environment.
• A collaborative mindset and a bias for action, effectively partnering with developers, architects, and adjacent teams to drive outcomes.

Bonus Points: Stand Out From the Crowd

• Master’s degree in Information Technology, Computer Science, Software Engineering, Artificial Intelligence, or a related degree, or equivalent practical experience.
• Experience in Test Driven Development, Behavior Driven Development, QA automation, and a quality engineering mindset and behaviors.
• Proficiency in creating architecture diagrams, design documentation, functional and technical specifications, automated test process documentation, runbooks, and production/test environment documentation.
• Experience with performance engineering, reliability testing, resiliency validation, and operational readiness for high-volume distributed platforms.
• Exposure to AI-assisted SDLC transformation initiatives, internal developer productivity programs, or enterprise AI implementation patterns.
• Experience supporting or mentoring peers on .NET engineering practices, cloud-native implementation, distributed systems, or responsible AI-assisted software delivery.