Full Stack AI Engineer
Backend Developer
Application Security
Artificial Intelligence
Automation
Azure
Cloud Data Engineering
Cloud Data Platform
Cloud Infrastructure
Cloud Native
Cloud Operations
Cloud Platform
Cloud Platforms
Cloud Platforms Cloud Platforms
Cloud Technology
Data Engineering
Data Platform
Data Science
DevOps
DevSecOps
Engineer
Engineering
Engineering Software
Full Stack
Generative AI
Google Cloud
Infrastructure As Code
Kubernetes
Machine Learning
Platform Engineering
Security Automation
Job Description
Build secure, scalable AI capabilities end-to-end to improve the advisor and client experience across Fidelity Wealth.
Responsibilities
- Design, build, and deliver AI-powered solutions from concept through production
- Partner with business stakeholders, product teams, architects, data scientists, and engineers to identify high-value AI opportunities
- Develop enterprise-grade AI capabilities focused on important business outcomes
- Translate business needs into practical AI applications through cross-functional collaboration
- Contribute to the evolution of modern AI platforms and capabilities
Requirements
- Bachelor’s degree or equivalent experience, with 3+ years of software engineering experience
- Proven track record designing and delivering scalable, production-grade software and distributed systems
- Experience applying LLMs and Generative AI technologies to address real business challenges
- Full-stack engineering background with modern languages and frameworks such as Python, TypeScript, Node.js, APIs, React, and Next.js
- Hands-on experience deploying and scaling applications in cloud environments including AWS, Azure, or Google Cloud
- Experience with platform engineering and DevOps practices, including containers, Kubernetes, Infrastructure-as-Code, and cloud-native architectures
- Strong understanding of software architecture, design patterns, and security, along with reliability principles for enterprise-scale applications
- Excellent problem-solving skills, sound technical judgment, and a passion for building innovative solutions
- Ability to collaborate effectively across engineering, data, product, and business teams while driving initiatives from concept to production
Technologies
- Python, TypeScript, Node.js
- APIs, React, Next.js
- LLMs, Generative AI
- AWS, Azure, Google Cloud
- Containers, Kubernetes
- Infrastructure-as-Code, cloud-native architectures
Example Use Cases
- Automated meeting preparation and research
- Intelligent call summarization and insight generation
- Automated follow-up and workflow orchestration
- Knowledge retrieval and recommendation systems
- AI-assisted decision support and productivity tools
- Workflow automation using enterprise data sources and communication channels