Sr. Agentic AI Platform Architect

Location: DFW Headquarters Building 8 (DFW-SV08) Fort Worth, TX 76155 (Hybrid) Durations:6-12+ Months with possible extension and conversions.

Interview Process: Two rounds - first virtual, second onsite

Job Overview: We are seeking a Senior Engineer 2 - Architect to join the Agentic System Layer (ASL) team. This individual will define and drive the technical architecture for an enterprise-scale agentic AI platform. The ideal candidate has hands-on experience designing and deploying production-grade AI and LLM-powered systems - not just prototypes. They should be comfortable leading architecture discussions, evaluating emerging AI frameworks, guiding engineering teams, and contributing code when needed to validate technical decisions.

Required: 10+ years of experience in software engineering and architecture. At least 3 years of experience designing AI/ML platform systems. Hands-on experience with LLM orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, or similar technologies. Strong knowledge of distributed systems, microservices architecture, event-driven systems, and scalable platform design. Advanced Python programming skills. Proficiency in at least one additional language, such as Java, Go, or TypeScript. Production experience building and deploying agentic AI systems or LLM-powered applications at scale. Experience with prompt engineering, tool-use patterns, RAG pipelines, LLM integration, and agent reliability. Strong understanding of observability, monitoring, testing, security, and failure-handling strategies for AI systems.

Preferred: Experience with Kubernetes and container orchestration. Experience with AWS, Azure, or Google Cloud Platform. Knowledge of MLOps or LLMOps tools and practices. Experience with vector databases such as Pinecone, Weaviate, or pgvector. Experience with knowledge graphs and graph-based retrieval. TOGAF or similar architecture certification.

Responsibilities: Design and evolve architectures for multi-agent orchestration systems, tool-use frameworks, and LLM integration pipelines. Establish patterns and standards for agent reliability, observability, security, scalability, and graceful degradation. Lead technical design reviews and create Architecture Decision Records (ADRs). Define API contracts, data-flow patterns, integration standards, and platform development guidelines. Collaborate with ML engineers, software engineers, product teams, and other technical stakeholders. Ensure platform components are scalable, secure, maintainable, and production-ready. Evaluate and integrate agentic AI frameworks such as LangGraph, LangChain, CrewAI, Semantic Kernel, and AutoGen. Design and implement patterns for prompt engineering, tool calling, RAG, LLM routing, memory, and agent evaluation. Identify architectural risks and recommend solutions for performance, reliability, cost, and maintainability. Mentor engineers on best practices for building and operating production-grade AI systems. Help establish standards for monitoring, logging, tracing, testing, and incident response across the AI platform. $000,000 - $000,000 Salary range is not shown on the candidate portal