Principal Software Engineer

About this role

At Fama, Principal Software Engineers are company-wide technical leaders who create leverage across the engineering organization, not just through the software they build, but through the systems, architectures, engineering practices, and AI-powered workflows they establish.

Success in this role is measured by long-term technical impact, engineering judgment, organizational influence, and the ability to simplify complex problems into durable, scalable solutions that accelerate product delivery and improve customer outcomes.

This role requires extensive use of AI-assisted and agentic development as a core engineering competency. Principal Software Engineers are expected to leverage AI throughout the software development lifecycle, including technical strategy, architecture, implementation planning, coding, testing, debugging, documentation, production operations, and organizational knowledge management. Beyond using AI effectively themselves, Principal Engineers are expected to design, build, and continuously improve AI agents and agentic engineering systems that increase the productivity and effectiveness of the entire engineering organization.

CORE RESPONSIBILITIES:

- Shape long-term technical strategy and architecture across products and platforms.

- Lead complex, cross-team initiatives from design through production.

- Establish engineering standards, architectural patterns, and best practices.

- Identify and address technical risks, scalability constraints, and operational complexity.

- Own the reliability, maintainability, and evolution of critical production systems.

- Lead resolution of complex production and customer-impacting issues.

- Mentor Engineers and raise the technical capabilities of the organization.

- Partner with engineering, product, operations, and leadership to align technical decisions with business priorities.

- Design and improve AI agents, engineering workflows, and automation that create organizational leverage.

- Evaluate AI-generated designs, code, tests, and documentation and remain accountable for their quality.

EXPERIENCE AND SKILLS

ORGANIZATIONAL TECHNICAL LEADERSHIP

- Demonstrated experience defining technical strategy across multiple teams or product domains.

- Proven ability to influence engineering organizations through technical leadership rather than organizational authority.

- Experience driving large-scale architectural initiatives from concept through long-term production ownership.

- Strong record of simplifying complex technical systems while improving engineering velocity and operational reliability.

- Demonstrated success mentoring Staff, Senior, and emerging technical leaders.

TECHNICAL EXPERTISE

- Deep expertise designing and operating highly scalable distributed systems and domain-oriented microservice architectures.

- Extensive experience with cloud-native platforms, infrastructure automation, and modern DevOps practices.

- Exceptional understanding of production operations, observability, monitoring, incident response, and system reliability.

- Strong architectural judgment across performance, security, maintainability, scalability, resilience, and cost optimization.

- Experience defining engineering standards, reusable frameworks, and shared platform capabilities.

AI-DRIVEN ENGINEERING

- Extensive experience using AI agents as a core part of software architecture, design, implementation, testing, debugging, and operational analysis.

- Demonstrated experience designing, building, and deploying AI agents or agentic workflows that improve engineering productivity or deliver customer-facing capabilities.

- Strong understanding of prompt engineering, context management, tool orchestration, evaluation frameworks, retrieval strategies, and AI system architecture.

- Experience establishing engineering standards and best practices for AI-assisted software development.

- Exceptional engineering judgment to validate, refine, and assume complete accountability for AI-generated designs, code, documentation, and operational decisions.

- Ability to identify where AI creates strategic advantage and where traditional engineering approaches remain the better solution.

COLLABORATION & LEADERSHIP

- Exceptional communication skills with the ability to influence technical and non-technical stakeholders, including executive leadership.

- Proven ability to build alignment across engineering, product management, operations, and business teams.

- Passion for developing engineers through mentorship, architectural guidance, and technical coaching.

- Comfortable operating with ambiguity while providing clarity and direction for others.

- Continuous learner who actively evaluates and adopts emerging engineering practices, AI technologies, and organizational improvements.

REQUIRED QUALIFICATIONS

- 10+ years of experience building backend applications with Python and FastAPI or similar framework.

- Expert knowledge of designing and implementing REST APIs and distributed microservice architectures.

- 5+ years architecting, deploying, and operating cloud-native applications using AWS serverless technologies and related cloud infrastructure.

- Demonstrated experience defining technical direction across multiple engineering teams or major platform initiatives.

- Proven ability to validate, refine, and take full ownership of AI-generated designs, code, tests, documentation, and architectural decisions before production deployment.

- Demonstrated experience working in an AI-first engineering environment where AI agents are a standard part of daily software development.

- Experience designing, building, and integrating AI agents or agentic workflows that automate engineering processes or power customer-facing products.

- Strong understanding of AI system architecture, prompt engineering, tool orchestration, context management, evaluation techniques, and operational gov

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