Full Stack AI Engineer

Fidelity TalentSource is seeking a Full Stack AI Engineer based in Covington, KY 41015 for an onsite role. This greenfield opportunity focuses on shaping and delivering AI engineering capabilities that strengthen the advisor and client experience across Fidelity Wealth.

You will design, build, and release secure, scalable, enterprise-grade AI solutions from early concept through production, working closely with technical and business partners to bring high-value ideas to real workflows.

Responsibilities

• Design, build, and deliver AI-powered solutions from concept through production.
• Partner closely with business stakeholders, product teams, architects, data scientists, and engineers to identify high-impact opportunities.
• Develop secure, scalable, enterprise-grade AI capabilities that drive meaningful business outcomes.
• Collaborate cross-functionally to translate business needs into practical AI applications.
• 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 experience designing and delivering scalable, production-grade software solutions and distributed systems.
• Experience applying LLMs and Generative AI technologies to address real business challenges.
• Full-stack engineering experience using modern languages and frameworks, including Python, TypeScript, Node.js, APIs, React, and Next.js.
• Hands-on deployment and scaling experience in cloud environments such as 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, security, and reliability 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 leveraging enterprise data sources and communication channels