Principal Software Engineer

Ascensus•Philadelphia, PA

About The Position

As a Principal Software Engineer, you will lead and hands-on contribute within a Scrum team to deliver complex solutions that align with our software architecture strategy, coding standards, and organizational policies. You will partner across disciplines to clarify requirements, make sound technical tradeoffs, and ship reliable software through a modern delivery pipeline focused on automation, quality, and frequent releases. You will mentor engineers, provide architecture and technical guidance in your areas of expertise, and continuously evaluate emerging technologies and practices—including AI-assisted engineering and intelligent automation—recommending adoption paths that strengthen delivery while meeting security, privacy, and enterprise governance expectations.

Requirements

Bachelor’s degree in computer science, engineering, or equivalent experience
Strong technical leadership with the ability to engage both technical and non-technical audiences and produce clear technical documentation and diagrams
Proficiency with modern AI coding and analysis tools (e.g., IDE assistants, chat-based models, automation) to accelerate development while maintaining quality, security, and accountability
Ability to design effective AI-assisted workflows, evaluate AI-generated output, and exercise sound judgment on when not to rely on automation
Experience integrating AI tooling into team standards (code reviews, testing, documentation) with appropriate guardrails for data handling, intellectual property, licensing, and regulated environments
Experience mentoring and coaching junior developers
Hands-on experience with C/C++, Python, Apache, Nginx, Redis, jQuery, PowerShell, or similar languages and platforms
Experience with modern JavaScript frameworks (React preferred; Angular, Knockout, or Bootstrap acceptable)
Experience with containerization and orchestration technologies, including Docker and Kubernetes
Experience maintaining and evolving legacy codebases
Strong understanding of object-oriented design principles, including SOLID, design patterns, data structures, and algorithms
Proven ability to write clean, maintainable code using best practices such as unit testing, TDD, CI/CD, automation, and refactoring
Strong experience with Agile SDLC methodologies
Excellent problem-solving, communication, and troubleshooting skills

Responsibilities

Analyze requirements and propose solutions that meet business goals; estimate and plan work across the Agile lifecycle.
Use AI where it helps to explore options, prototype, and surface risks—then ground decisions in constraints and evidence.
Implement complex changes to the codebase using team standards, source control, unit testing, and CI/CD.
Use AI-assisted coding to move faster without sacrificing quality: small increments, clear intent, peer review, and tests that prove correctness.
Diagnose complex application issues to root cause and resolution.
Use AI to suggest hypotheses or steps when useful; confirm with logs, metrics, and reproducible evidence.
Support testing and clear written descriptions of changes.
Use AI to speed drafting of cases, scenarios, or docs; engineers own accuracy, completeness, and customer clarity.
Collaborate in Scrum activities, pair programming, and code review; help refine team norms for AI-assisted work (reviews, secure usage, quality gates) as part of continuous improvement.
Work with the Product Owner to understand and influence the roadmap, with ownership for architecture and technical delivery—including automation and AI-enabled capabilities that fit enterprise governance and non-functional requirements.
Lead or support technical research and innovation: evaluate platforms, models, tooling, and integration patterns; participate in architecture discussions with a consistent lens on security, privacy, model lifecycle, and operations.
Lead by example as coach and mentor; give steady feedback on technical and architectural choices, incidents, and safe rollout of AI-related changes (evaluation, monitoring, guardrails).
Protect Ascensus confidential information and follow approved AI and data-handling policies so data is not exposed, mis-transmitted, or disclosed without authorization.
Demonstrate the I-Client philosophy and Core Values—People Matter, Quality First, and Integrity Always®—including transparent, ethical use of AI that earns trust with clients and colleagues.