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

Fidelity Investments•Covington, KY

About The Position

The Senior Full Stack Engineer will help deliver business-unit-wide technology solutions by researching and recommending appropriate models, methods, tools, and technologies, and by contributing to technology strategy in partnership with business stakeholders. The role designs, builds, and supports runtime services, platforms, and applications that power AI-enabled experiences at scale, while identifying and mitigating technical risks. The engineer will join the team responsible for creating and supporting Fidelity’s Cognitive Computing Platform, which enables customers to interact with Fidelity in natural language across relevant channels. The role focuses on reliable runtime services and operational practices for consistently and safely running AI-enabled solutions, 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 includes building scalable solutions on a scrum team for multiple business units, collaborating across an empowered organization, promoting quality and sustainability through automation, sharing knowledge through code reviews and design discussions, and helping teams operationalize GenAI solutions reliably, safely, and repeatably. Fidelity’s onsite work model is transitioning through a phased regional and role-based rollout; specific onsite expectations vary and may evolve. Fidelity will not provide immigration sponsorship for this position.

Requirements

Broad experience across the software development and delivery lifecycle, including design, implementation, 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 frontend 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 operationally minded production system development.
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 methodologies and cross-functional collaboration to deliver iterative value.
Ability to synthesize business needs into scalable technology solutions.
Ability to work across organizations and drive positive outcomes.
Comfort working 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

Exposure to major cloud platforms such as AWS, GCP, or Azure, including cloud-native services, deployment pipelines, and distributed architectures.
Working knowledge of LLM concepts, including prompting patterns, token limits, and latency considerations.
Understanding of Retrieval-Augmented Generation (RAG) fundamentals and embedding-based search.
Knowledge of model evaluation basics for quality, safety, and regression testing using evaluation frameworks and benchmark datasets.
Understanding 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 for business-unit-wide solutions.
Contribute to technology strategy in partnership with stakeholders across the business.
Design, build, and support runtime services, platforms, and applications for AI-enabled experiences at scale.
Identify and mitigate technical risks in delivered solutions.
Create and support the Cognitive Computing Platform and reliable runtime services for natural-language customer interactions.
Build scalable solutions on a scrum team that benefit multiple business units.
Collaborate across organizations and with data science and product teams to operationalize AI use cases.
Contribute to quality and sustainability through automation.
Share knowledge and provide technical guidance through code reviews and design discussions.
Help operationalize GenAI solutions with attention to reliability, safety, and repeatability.