Principal Software Engineer (Agentic Dev Specialist)

Praxent is a company focused on transforming the financial services sector by modernizing outdated software applications. As a Principal Software Engineer, you will lead development teams to establish technical standards and architecture for AI solutions, ensuring they align with business goals and deliver high-impact results.

Responsibilities:

• Lead development teams to ensure sprint commitments are met
• Establish Technical Standards & Architecture
• Define and maintain AI technical standards, reference architectures, prompt libraries, templates, and playbooks
• Support the creation and evolution of AI enabled SDLC frameworks with developers that teams can reliably apply across projects
• Lead architecture reviews and act as a quality gate for AI design decisions
• Support Presales AI Solutioning
• Partner with sales and delivery to design AI strategies, architectures, and proof of concepts
• Translate client needs into compelling technical narratives and implementation plans
• Serve as a trusted technical voice during early stage client engagements
• Design & Implement MLOps Platforms
• Architect and deploy MLOps/AIOps platforms that support model lifecycle management, evaluation, and monitoring
• Optimize performance, cost, and reliability across AI deployments
• Ensure AI solutions are secure, observable, and production ready
• Elevate Training & Delivery Quality
• Develop and deliver AI training programs, workshops, and internal documentation
• Maintain AI standards and learning content within internal platforms
• Mentor engineers and delivery leads on AI trade-offs, risks, and best practices
• Define AI architecture patterns and review project implementations
• Create reusable AI frameworks, prompts, and playbooks
• Support presales efforts with technical designs and client-facing explanations
• Coach teams through architectural decisions and delivery challenges
• Collaborate cross-functionally to align AI initiatives with business outcomes

Requirements:

• Deep experience designing and delivering AI enabled systems in production
• Strong background in MLOps, model lifecycle management, and evaluation frameworks
• Proficiency with modern AI/ML frameworks and cloud based AI platforms
• 8–12+ years of professional experience in software engineering and system architecture
• Proven ability to design scalable, secure, and maintainable systems
• In depth experience with end-to-end full stack architectures, modernizing legacy systems into scalable, cloud-ready solutions while leveraging AI/ML capabilities (e.g., LLMs, automation, intelligent workflows) to improve performance, maintainability, and business outcomes
• Experience improving delivery efficiency through standards and tooling
• Comfortable presenting complex AI concepts to technical and non-technical stakeholders
• Ability to connect AI capabilities to measurable business value
• Demonstrated experience mentoring engineers and elevating team capabilities
• Passion for building shared understanding and continuous improvement
• Relevant Education May include intensive programs, Bachelor's degree in Computer Science, Engineering, or equivalent experience
• Values Alignment: We Care Deeply, Always Deliver, Never Settle, Do It Together, Own the Outcome, and approach every situation with a CAN DO mentality