Agentic Engineering Specialist
TIAA is seeking an Agentic Engineering Specialist to design and build the AI-driven backbone of our enterprise data estate. This is a hands-on builder role for a hardcore engineer with real-world AI experience—someone who lives at the intersection of applied AI and production systems engineering.
This Role will design and ship intelligent agents, agentic workflows, and LLM-powered capabilities that operate across a heterogeneous data landscape spanning graph, vector, and document databases. You will bring engineering rigor to a domain that often lacks it, taking agentic systems from concept through production deployment while navigating the operational realities of running LLMs at scale.
Key Duties & Responsibilities
- Design, build, and ship AI agents and agentic workflows into production environments, moving well beyond prototypes and proofs of concept
- Design systems that synthesize and reconcile data across graph, document (MongoDB), 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 agent iteration and self-correction loops that are both reliable and bounded
- Build and optimize RAG architectures using orchestration frameworks such as LangChain and LangGraph
- Apply deep 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
- Bring strong software engineering discipline—robust testing, CI/CD, and source control practices—to AI system development
Educational Requirements
- University (Degree) Preferred
Work Experience
- 5+ Years Required; 7+ Years Preferred
Career Level
9IC
Required Skills:
- 5 years’ experience with Full Stack Development
- Experience with multiple database types: graph, vector, document, and/or relational databases.
Preferred Qualifications:
- 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
Related Skills
Agile Methodology, Continuous Integration and Deployment, Data Analysis, Debugging, DevOps, Enterprise Application Integration, Operating Systems Management, Problem Solving, Programming, Software Development, Software Development Life Cycle, Web Application Development
Anticipated Posting End Date:
2026-10-13
Base Pay Range: $170,000/yr - $245,000/yr
Actual base salary may vary based upon, but not limited to, relevant experience, time in role, base salary of internal peers, prior performance, business sector, and geographic location. In addition to base salary, the competitive compensation package may include, depending on the role, participation in an incentive program linked to performance (for example, annual discretionary incentive programs, non-annual sales incentive plans, or other non-annual incentive plans).
_____________________________________________________________________________________________________
