Senior AI Engineer; Agentic Systems

Senior AI Engineer (Agentic Systems)

Location:

Plano, TX (Onsite)

Employment Type:

Contract

Contract Duration: 12 Months

This role emphasizes deep AI engineering expertise and the autonomous ownership of an enterprise-scale agentic microservice. The position requires an individual who can identify, prioritize, and drive work independently to contribute from day one. You will own and lead the design, development, and evolution of the microservice, build robust multi-agent orchestration frameworks, and integrate LLMs to automate complex decision-making.

• Architect and develop Lang Chain/Lang Graph-based multi-agent systems for enterprise workloads.
• Design and expose backend services and orchestration APIs using FastAPI and Python.
• Engineer scalable agentic workflows capable of processing and reasoning over large volumes of data.
• Build and optimize Retrieval-Augmented Generation (RAG) workflows integrating vector databases and relational data stores.
• Apply expert-level prompt and context engineering techniques to maximize LLM reliability and performance.
• Implement observability, telemetry, and monitoring instrumentation to ensure the operational health of agentic services.
• Maintain high code quality standards using Python best practices and Pydantic for data validation.
• Proactively identify technical debt, architectural gaps, and new work streams, owning them through to completion.

Experience:

5+ years of software engineering experience with a strong focus on AI/ML engineering and backend systems. Deep hands-on experience with Lang Chain and Lang Graph for building agentic and multi-agent systems is required.

Technical

Skills:

Expertise in Python and Pydantic is necessary. A strong understanding of Large Language Models (LLMs), including architecture, behavior, limitations, and prompt engineering, is essential. Experience integrating vector databases into RAG workflows, particularly Elasticsearch, is strongly preferred. Candidates must have demonstrated ability to design agentic workflows that handle big data processing and experience building and consuming RESTful APIs with FastAPI.

Other

Qualifications:

Must be self-directed and autonomous, with the ability to own a service end-to-end and execute without heavy oversight. A conceptual understanding of LLM fine-tuning and training concepts is required.

• Frontend experience with React, HTML, and/or Type Script.
• A background in Data Science or familiarity with data pipelines and analytics.
• Experience with Lang Smith for LLM tracing, debugging, and evaluation.
• Experience with Galileo for LLM observability and monitoring.
• Experience working in enterprise or financial services engineering environments.