Principal Software Engineer, Applied AI

FactSet • Norwalk, CT

4d • $180,000 - $235,000

About The Position

FactSet is seeking a Principal Software Engineer to design, build, and ship AI-powered products using large language models (LLMs) and agentic technologies. The role focuses on moving quickly from prototype to production and turning emerging AI capabilities into reliable, high-quality solutions for clients. The engineer will serve as a technical leader, establish engineering standards for applied AI, mentor other engineers, and help shape FactSet’s AI product portfolio.

The position calls for deep software engineering expertise and hands-on experience building LLM-based and agentic systems, including orchestration, tool use, retrieval, evaluation, and observability. The engineer will use AI-assisted development tools such as Claude Code and apply practices across the AI-driven development lifecycle, including planning, development, review, testing, and deployment. The role involves working autonomously in a fast-paced, evolving environment while collaborating across product and engineering teams and contributing to product and platform direction.

Requirements

• Bachelor’s degree in computer science or a relevant field.
• 8–10+ years of experience developing, testing, and deploying high-quality, stable software, with a consistent record of delivering on time.
• Hands-on experience building and deploying applications using LLMs and agentic technologies, such as prompt engineering, RAG, function or tool calling, agent orchestration frameworks, and MCP or similar protocols.
• Hands-on familiarity with AI coding assistants such as Claude Code and a strong understanding of the AI-driven development lifecycle, including how planning, implementation, review, testing, and deployment change when AI agents participate.
• Strong software architecture and design skills, including experience building scalable, observable, and maintainable systems.
• Experience designing evaluation approaches for non-deterministic systems and iterating on quality using data.
• Ability to give and receive code review feedback and contribute forward-looking design ideas.
• Ability to mentor and coach engineers in effective use of AI coding assistants and help establish AI development standards and guardrails for a team or organization.
• Ability to articulate FactSet’s business, client base, and how the work fits into the broader picture.

Nice To Haves

• Experience with financial data, analytics, or investment workflows.
• Familiarity with cloud platforms, containerization, and modern MLOps or LLMOps practices.
• Experience with model evaluation, fine-tuning, or optimization for latency and cost.
• Experience building custom tooling for AI-assisted development, such as MCP servers, reusable skills, subagents, or agent configuration conventions.
• Contributions to AI developer tooling, internal platforms, or open-source projects.
• Ability to thrive in dynamic environments by adapting to shifting requirements and quickly learning new models, tools, and practices.
• Excellent communication skills and ability to collaborate across teams and influence without direct authority.
• Track record of mentoring engineers and raising team standards.

Responsibilities

• Design, develop, test, and deploy production-grade LLM and agentic applications, including multi-step agents, tool calling, retrieval-augmented generation, and workflow orchestration.
• Deliver stable, high-quality features that follow best practices in testing, CI/CD, and operational readiness.
• Build and maintain evaluation frameworks, guardrails, and monitoring to improve AI feature quality, safety, latency, and cost.
• Prototype emerging approaches and harden successful solutions for production.
• Use AI coding assistants and agentic workflows to accelerate delivery while maintaining quality, security, and maintainability.
• Lead code and design reviews, including rigorous evaluation of AI-generated code.
• Mentor engineers on applied AI patterns, agent design, and effective use of AI coding assistants, including prompting, task decomposition, and output verification.
• Define and evolve team standards for AI-assisted development, including code review, testing, security, and responsible use of AI tooling.
• Stay current with LLMs, agent frameworks, and developer tooling and translate relevant advances into team practices.
• Partner with product managers, designers, architects, direct managers, and engineering peers to define solutions and scope.
• Plan and drive projects, communicating tradeoffs, risks, and progress to technical and non-technical stakeholders.
• Respond to bugs, incidents, and feature requests throughout the development and feedback lifecycle.
• Diagnose and resolve AI-specific issues, including non-deterministic behavior, hallucinations, model regressions, and prompt or tool failures.
• Lead and participate in architecture discussions and brainstorming to shape features and platform capabilities.
• Evaluate and introduce AI-enabled development tools and workflows to improve team productivity and product quality.
• Develop deep proficiency in FactSet products and data and contribute to the direction of its AI strategy.

Benefits

• Health, life, and disability insurance.
• Retirement savings plans.
• Discounted employee stock purchase program.
• Paid time off for holidays and family leave.
• Flexible “moments that matter” days.
• Flexible work accommodations.
• Career progression planning and dedicated monthly learning and development time.
• Business Resource Groups open to all employees.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal