AI Engineer

Dynasty Financial Partners, LLC•St. Petersburg, FL

just now•Onsite

About The Position

Dynasty Financial Partners is building AI-powered systems that directly support advisors, operations teams, and client-facing platforms. We are looking for an AI Engineer to design, build, and operate production-grade AI systems — including LLM-powered agents, RAG pipelines, and evaluation frameworks — that are secure, reliable, and measurable in real business impact. You will work closely with product managers, data engineers, and software engineers in an agile environment, owning AI solutions end-to-end: from architecture and experimentation through deployment, monitoring, and iteration. This role reports to the Director of Engineering. Please Note: This job is an IN-OFFICE position located in St. Petersburg, FL. If you are unable or unwilling to fulfill this requirement of the position, please refrain from applying

Requirements

Experience: 2–5 years of hands-on experience in software development, including at least 1–2 years building GenAI-driven applications.
Multi-Agent Systems: Proven experience implementing or integrating agent-based AI systems and workflows. Familiarity with one or more multi-agent orchestration frameworks such as n8n, Microsoft Co-Pilot Studio, LangChain, or LangGraph is required. You should understand agent architectures and how to coordinate multiple AI agents towards a goal.
LLMs & RAG Proficiency: Hands-on experience working with large language models and RAG techniques. Ability to design RAG pipelines and knowledge management systems – e.g. creating embeddings, configuring vector databases, and applying chunking strategies to manage context window. Strong grasp of prompt engineering and tuning to guide LLM behavior.
Technical Skills: Proficient in building back-end services and integrations for AI solutions. Solid programming skills in Python, .NET or Java. Familiarity with data structures for semantic search and knowledge integration (experience with databases like Pinecone, Weaviate, or Azure AI Search beneficial).
Excellent communication skills, ability to work with non-technical people.

Responsibilities

Collaborate & Innovate: Work closely with internal stakeholders, product managers, data engineer, and software engineers to identify opportunities for AI automation. Communicate complex AI system behaviors and limitations to non-technical stakeholders. Stay up-to-date with the latest advancements in LLMs, agent frameworks, and AI orchestration tools, continuously bringing new ideas to improve our multi-agent systems.
Design & Orchestrate AI Agents: Develop and implement complex multi-agent workflows to solve business problems, using orchestration frameworks to coordinate LLM-powered agents and tools. This includes defining agent roles, interaction logic, and QA processes.
Design RAG Pipelines and build Knowledge Systems: Work with our Data Engineering team to build and optimize RAG pipelines to give AI agents access to knowledge.
Integrate & Deploy Solutions: Work with engineers to integrate AI agents into our products and workflows.
Monitor & Safeguard AI Performance: Establish evaluation frameworks to continuously assess and improve agent performance (accuracy, relevance, response time). Implement automated testing, monitoring, and logging for AI interactions. Proactively incorporate guardrails (input validation, output filters, safety checks) to ensure responses meet quality and ethical standards.