Principal Software Development Engineer

Enlyte•UNAVAILABLE, UNAVAILABLE

6d•Remote

About The Position

This is a full-time remote position that can be located anywhere in the U.S. The Principal Software Development Engineer will serve as the technical authority for financial systems, billing platforms, and data solutions. They will define and maintain architectural standards, engineering principles, and technology strategies, while designing scalable, secure, highly available, and resilient distributed systems. This role involves leading architecture reviews, providing technical guidance across multiple engineering teams, and identifying/mitigating technical risks. The engineer will also architect and evolve data ingestion pipelines, design and optimize high-volume transaction processing systems, guide development of cloud-native solutions on AWS, and ensure platform observability, performance, scalability, reliability, and operational excellence. A key aspect of this role is championing the adoption of Artificial Intelligence solutions, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI Systems, and AI-assisted software engineering practices. They will also establish and promote best practices for software architecture, design patterns, testing, security, and DevOps, mentor engineers, foster a culture of innovation, and lead incident response efforts. Collaboration with executives, business stakeholders, and engineering leadership to align technology investments with strategic goals is crucial, as is translating complex technical concepts into business-focused recommendations and influencing enterprise technology decisions.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
10+ years of professional software engineering experience.
5+ years of experience providing technical leadership across multiple teams or large-scale platforms.
Expert-level experience with Python.
Expert-level experience with C# and .NET Core.
Deep expertise in software architecture and distributed systems design.
Strong experience building cloud-native applications on AWS.
Advanced knowledge of PostgreSQL, Snowflake, and data platform architectures.
Extensive experience with SQL optimization, data modeling, and enterprise-scale data solutions.
Experience implementing event-driven architectures and microservices.
Experience leading large-scale modernization or transformation initiatives.
Hands-on experience with AI technologies, including LLMs, RAG, Agentic AI, or AI-powered enterprise solutions.

Nice To Haves

Experience with NetSuite and Salesforce integrations.
Experience with Low-Code platforms such as OutSystems.
Experience with financial systems, billing platforms, pricing engines, or revenue management solutions.
Experience building enterprise data lakes, analytics platforms, or data mesh architectures.
Experience establishing engineering standards and influencing technical direction across organizations.

Responsibilities

Serve as the technical authority for financial systems, billing platforms, and data solutions.
Define and maintain architectural standards, engineering principles, and technology strategies.
Design scalable, secure, highly available, and resilient distributed systems.
Lead architecture reviews and provide technical guidance across multiple engineering teams.
Identify and mitigate technical risks while balancing business objectives and long-term sustainability.
Architect and evolve data ingestion pipelines supporting operational and analytical workloads.
Design and optimize high-volume transaction processing systems and pricing engines.
Guide development of cloud-native solutions leveraging AWS services and serverless architectures.
Ensure platform observability, performance, scalability, reliability, and operational excellence.
Drive modernization initiatives across applications, infrastructure, integrations, and data platforms.
Champion adoption of Artificial Intelligence solutions, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI Systems, and AI-assisted software engineering practices.
Identify and implement AI-driven capabilities that improve automation, operational efficiency, and business value.
Partner with Data Science teams to operationalize machine learning and advanced analytics solutions.
Establish and promote best practices for software architecture, design patterns, testing, security, and DevOps.
Conduct technical design reviews and mentor engineers at all levels.
Foster a culture of innovation, accountability, collaboration, and continuous improvement.
Drive engineering productivity through automation, low-code solutions, and platform tooling.
Lead incident response efforts for critical production issues and drive root-cause resolution.
Collaborate with executives, business stakeholders, and engineering leadership to align technology investments with strategic goals.
Translate complex technical concepts into business-focused recommendations.
Influence enterprise technology decisions and investment priorities.
Contribute to organizational technical strategy and long-term platform planning.