Principal, Full Stack Engineer (Node, Python, Angular/ React)

Fidelity Investments•Covington, KY

10d

About The Position

Fidelity is seeking a Principal, Full Stack Engineer to help deliver its Cognitive Computing Platform, which enables customers to interact with Fidelity in natural language across relevant channels. The role develops, researches, and recommends models, methods, tools, and technologies to support business-unit-wide solutions, contributes to technology strategy with business stakeholders, and designs, builds, and supports runtime services, platforms, and applications for AI-enabled experiences at scale. The engineer also helps identify and mitigate technical risks. As part of the team responsible for creating and supporting the platform, this role delivers reliable runtime services and operational practices that help teams run AI-enabled solutions consistently and safely, including dynamic experiences rendered within conversational chat. The team builds intuitive, engaging conversational experiences that help customers manage their finances and make confident choices. The role works in an empowered, cross-functional environment, delivering scalable solutions across business units and helping operationalize GenAI use cases with a focus on reliability, safety, and repeatability. Fidelity describes its work model as transitioning to full-time onsite through a phased regional and role-based rollout; onsite requirements currently vary, and may evolve.

Requirements

Broad experience across the software development and delivery lifecycle, from design and implementation through testing, deployment, and ongoing support.
Strong engineering proficiency in Node.js and Python, including designing and implementing scalable, maintainable backend services.
Experience building enterprise-grade conversational and interactive UI components using React or Vue, and hands-on experience with front-end testing frameworks such as Jest, Cypress, or Playwright.
Hands-on experience with NoSQL data stores such as MongoDB, DynamoDB, or ElastiCache, including data modeling and performance optimization.
Grounding in DevOps/SRE practices, including monitoring, alerting, incident response, reliability engineering, and an operational mindset for production systems.
Experience designing and consuming RESTful APIs, using service-oriented architecture, and applying object-oriented programming principles.
Familiarity with OpenAPI/Swagger and structured JSON-based service contracts, including versioning and documentation practices.
Practical experience with Agile development methodologies and cross-functional collaboration.
Exposure to major cloud platforms such as AWS, GCP, or Azure, including cloud-native services, deployment pipelines, and distributed architectures.
Strong desire and ability to learn new technologies and approaches.
Ability to synthesize business needs into scalable technology solutions.
Ability to work across organizations and drive positive outcomes.
Comfort operating in a polyglot development environment.
Excellent verbal and written communication skills.
Ability to collaborate with data science and product teams to operationalize AI use cases.

Nice To Haves

Working knowledge of LLM concepts, including prompting patterns, token limits, and latency considerations.
Knowledge of Retrieval-Augmented Generation (RAG) fundamentals and embedding-based search concepts.
Understanding of model evaluation basics, including quality, safety, and regression testing using evaluation frameworks and benchmark datasets.
Knowledge of responsible AI practices, including guardrails, privacy considerations, and secure usage patterns.
Operational awareness for GenAI solutions, including cost, performance, reliability, and safe usage.
Understanding of observability for LLM-based applications, including logging, metrics, and tracing at prompt and inference layers.
Undergraduate degree (BS, BA, etc.) or equivalent work experience.
Relevant cloud, DevOps/SRE, or AI/ML certifications.

Responsibilities

Develop, research, and recommend models, methods, tools, and technologies to achieve business-unit-wide solutions.
Contribute to technology strategy in partnership with stakeholders across the business.
Design, build, and support runtime services, platforms, and applications that power AI-enabled experiences at scale.
Identify and mitigate technical risks in delivered solutions.
Create and support the Cognitive Computing Platform and its reliable runtime services and operational practices.
Build scalable solutions on a scrum team that benefit multiple business units.
Work across an empowered and autonomous organization to achieve strong outcomes.
Contribute to a developer culture of quality and sustainability through automation.
Share knowledge and provide technical guidance to peers through code reviews and design discussions.
Help teams operationalize GenAI solutions with attention to reliability, safety, and repeatability.
Collaborate with data science and product teams to operationalize AI use cases.