Sr. AI Engineer

Saxon Global•Covington, KY

4d•Onsite

About The Position

As an early member of this organization, you will play a key role in designing, building, and delivering AI-powered solutions from concept through production. This position offers the opportunity to collaborate closely with business partners, product teams, architects, data scientists, and fellow engineers to identify high-value opportunities and develop secure, scalable, enterprise-grade AI capabilities that drive meaningful business outcomes. This role is ideal for a hands-on Sr. AI Engineer who thrives at the intersection of AI, software engineering, data engineering, and cloud technologies. Successful candidates will possess strong technical expertise and a passion for building innovative solutions, partnering with cross-functional teams to translate business needs into practical AI applications. The ideal individual enjoys solving complex technical challenges, developing production-ready systems, and contributing to the evolution of modern AI platforms and capabilities. This is a unique Greenfield opportunity to help build a brand-new AI engineering organization focused on delivering innovative AI solutions that enhance the advisor and client experience across Fidelity Wealth. The team's mission is to leverage artificial intelligence, automation, advanced analytics, and large language models (LLMs) to tackle real business problems, streamline advisor workflows, reduce administrative overhead, and help advisors spend more time delivering value to clients. Representative initiatives may include developing AI-powered capabilities that improve advisor effectiveness and client engagement, such as: 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

Requirements

Bachelor's degree or equivalent experience with 5+ years of software engineering experience.
Proven experience designing and delivering scalable, production-grade software solutions and distributed systems.
Deep expertise building AI-powered applications utilizing large language models (LLMs), agent frameworks, and orchestration platforms (e.g., OpenAI, Claude, Bedrock, LangChain, LangGraph).
Experience developing Retrieval-Augmented Generation (RAG) solutions, semantic search capabilities, and enterprise knowledge systems leveraging vector databases and retrieval frameworks.
Strong 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 within cloud environments such as AWS, Azure, or Google Cloud.
Experience with modern 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 principles for enterprise-scale applications.
Excellent problem-solving skills, sound technical judgment, and a passion for building innovative solutions.
Ability to collaborate optimally across engineering, data, product, and business teams while driving initiatives from concept to production.

Nice To Haves

AI & LLM Engineering (OpenAI, Claude, Gemini, Bedrock, LangChain, LangGraph, CrewAI, Python, AI Agents, RAG, Prompt Engineering, Workflow Automation)
Data Engineering & AI Data Foundations (Snowflake, Databricks, Data Pipelines, ETL/ELT, Pinecone, Weaviate, Chroma, Semantic Search, Knowledge Retrieval, Enterprise Data Architecture)
Cloud Architecture, Scale & Security (AWS, Azure, Docker, Kubernetes, Terraform, Cloud-Native Platforms, Microservices, Security, Scalability)

Responsibilities

Designing, building, and delivering AI-powered solutions from concept through production.
Collaborating closely with business partners, product teams, architects, data scientists, and fellow engineers to identify high-value opportunities.
Developing secure, scalable, enterprise-grade AI capabilities that drive meaningful business outcomes.
Translating business needs into practical AI applications.
Developing production-ready systems.
Contributing to the evolution of modern AI platforms and capabilities.
Leveraging artificial intelligence, automation, advanced analytics, and large language models (LLMs) to tackle real business problems.
Streamlining advisor workflows.
Reducing administrative overhead.
Helping advisors spend more time delivering value to clients.
Developing AI-powered capabilities that improve advisor effectiveness and client engagement.
Designing and delivering scalable, production-grade software solutions and distributed systems.
Building AI-powered applications utilizing large language models (LLMs), agent frameworks, and orchestration platforms.
Developing Retrieval-Augmented Generation (RAG) solutions, semantic search capabilities, and enterprise knowledge systems leveraging vector databases and retrieval frameworks.
Deploying and scaling applications within cloud environments.
Implementing modern platform engineering and DevOps practices.
Collaborating effectively across engineering, data, product, and business teams.
Driving initiatives from concept to production.