Top Consulting Software Engineer Jobs in New York City, NY

Lead the design and implementation of an Internal Developer Portal. Mentor engineers, drive automation standards, and enhance engineering productivity for Mastercard's software development teams.

The Principal Software Architect leads technical direction across teams, advocating for architectural excellence and mentoring engineers while addressing complex technical challenges and fostering collaboration.

As an Engineering Specialist, you will design and implement cloud-based data solutions, guide architecture decisions, and mentor teams in data engineering practices, primarily using Databricks and AWS.

Oversee software engineering projects, lead large-scale distributed data processing systems, mentor junior staff, and drive project success.

The Forward Deployed Software Engineer will work with clients to build and maintain applications that solve business problems, enhance workflows, and drive value quickly. The role emphasizes collaboration, independent problem-solving, and a focus on customer success.

Design, develop and deliver full stack applications using Java, AngularJS, and SQL, while collaborating in engineering pods through the software development lifecycle.

The role involves architecting and delivering scalable integration solutions with Boomi, engaging clients, managing projects, and mentoring junior staff while driving business development efforts.

As a Senior GenAI Solutions Architect, you will lead the design and implementation of generative AI applications on AWS, collaborating with clients to understand their needs and guiding project execution with a team of engineers.

Design and optimize low-latency, high-throughput backend systems in payments processing using Java, while leading architectural changes and mentoring peers.

The Salesforce Developer will implement and optimize Revenue Cloud solutions, including CPQ and Billing, ensuring accurate quoting and compliance with revenue standards.

The AI Data Engineer will design and implement data pipelines, build AI-optimized data infrastructure, ensure data quality, and collaborate with teams to support AI applications.