Agentic Engineering Specialist

TIAA • Charlotte, NC

1d • Onsite

About The Position

TIAA is seeking a hands-on Agentic Engineering Specialist to design and build the AI-driven backbone of its enterprise data estate. The role combines applied AI and production systems engineering, developing intelligent agents, agentic workflows, and LLM-powered capabilities across graph, vector, and document databases. The specialist will bring engineering discipline to agentic systems from concept through production deployment, accounting for the operational challenges of running LLMs at scale.

The position requires full-stack development experience and experience with multiple database types, including graph, vector, document, and/or relational databases. Five years of full-stack development experience are required; seven or more years are preferred. A university degree is preferred. The role is listed as Career Level 9IC.

TIAA describes its work culture as collaborative and in-office, with teams working across organizational boundaries. Its compensation package includes a base salary range of $170,000 to $245,000 per year. Depending on the role, compensation may also include participation in performance-linked incentive programs. Benefits include a retirement program and health, wellness, and work-life offerings.

Requirements

• At least 5 years of full-stack development experience.
• Experience with multiple database types, including graph, vector, document, and/or relational databases.

Nice To Haves

• A university degree is preferred.
• At least 7 years of work experience is preferred.
• Experience building agentic AI solutions.
• Experience with MCP (Model Context Protocol), CrewAI, or similar emerging agentic frameworks.
• Familiarity with Redis for caching, session state, or short-term memory implementations.
• Experience with cloud-native deployment on OpenShift or Kubernetes.
• Exposure to code modernization tooling such as Moderne.
• Full-stack development experience.
• Prior experience mentoring or setting technical direction for a team.

Responsibilities

• Design, build, and ship AI agents and agentic workflows into production environments, beyond prototypes and proofs of concept.
• Design systems that synthesize and reconcile data across graph, MongoDB document, and vector data sources into coherent, reliable outputs.
• Develop memory and context management strategies for LLM applications, including context-window optimization and multi-turn state handling.
• Engineer reliable, bounded agent iteration and self-correction loops.
• Build and optimize retrieval-augmented generation (RAG) architectures using orchestration frameworks such as LangChain and LangGraph.
• Apply expertise in graph database query languages, data modeling, and performance tuning to support agentic reasoning at scale.
• Design and implement agents using Agent Core or comparable agentic frameworks.
• Optimize prompt engineering and LLM interaction patterns for cost, latency, and output quality.
• Apply software engineering practices, including robust testing, CI/CD, and source control, to AI system development.

Benefits

• Superior retirement program.
• Competitive health, wellness, and work-life offerings.
• Potential participation in performance-linked incentive programs, depending on the role.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior