Principal Agentic AI Architect

Section

Details

Principal Agentic AI Architect

Full Time

Irving, TX

Onsite

Full Time

$120-$150k/yr.

• Principal Agentic AI Architect responsible for designing and delivering enterprise-grade agentic AI platforms and intelligent multi-agent systems that solve complex business problems.
• Leads the architecture and technical strategy for LLM-powered agents, multi-agent orchestration, advanced RAG, tool/function calling, agent memory, planning, reasoning, and autonomous workflow execution.
• Partners with engineering, product, data, security, and business teams to translate requirements into scalable AI solutions.
• Drives adoption of LLMs, prompt engineering, vector databases, embeddings, knowledge retrieval, model evaluation, AI/ML pipelines, and cloud-native AI services while establishing architecture standards for security, governance, observability, reliability, and responsible AI.
• Provides technical leadership across the full AI lifecycle, from architecture and prototyping through production deployment, optimization, monitoring, and continuous improvement

• Lead the architecture, design, and engineering of a next-generation Agentic AI Harness for Banking capable of supporting 50+ enterprise AI use cases.
• Evolve the existing agent framework into a scalable, extensible, and enterprise-grade agentic platform aligned with future business needs.
• Define and own the end-to-end architecture covering orchestration, tool integration, memory management, context management, document intelligence, observability, security, and governance.
• Provide technical leadership and hands-on engineering guidance across all components of the Agentic AI platform.
• Design reusable services, frameworks, and platform capabilities to accelerate onboarding of new AI use cases and business domains.
• Establish architectural standards, reference patterns, engineering best practices, and platform roadmaps.
• Collaborate with C-Suite leadership, enterprise architects, AI engineers, and business stakeholders to drive platform adoption and innovation.
• Evaluate emerging Agentic AI technologies, frameworks, and industry trends, recommending strategic enhancements to the platform.

• 12+ years of software engineering experience, including 5+ years designing and building enterprise AI/ML platforms.
• Proven experience architecting and delivering large-scale AI solutions, Agentic AI systems, AI platforms, or multi-agent frameworks in enterprise environments.
• Deep understanding of the Agentic AI ecosystem including agent orchestration, planning, reasoning, tool calling, memory management, retrieval systems, and autonomous workflows.
• Hands-on expertise building AI applications using frameworks and platforms such as Google ADK, LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, or similar agentic frameworks.
• Strong experience designing scalable orchestration layers, tool libraries, context management frameworks, observability solutions, and governance controls for AI systems.
• Expertise in Retrieval-Augmented Generation (RAG), vector databases, embeddings, enterprise knowledge systems, and document intelligence platforms.
• Experience designing extensible and reusable AI platform architectures capable of supporting multiple business use cases and domains.
• Strong software engineering background in cloud-native architectures, distributed systems, APIs, microservices, and platform engineering.
• Deep understanding of AI observability, monitoring, evaluation frameworks, model governance, security, and responsible AI principles.
• Exceptional communication and stakeholder management skills with the ability to influence senior technology leaders and architects.
• Architect and optimize core platform components including:
• Agent Orchestration Layer
• Tool Library Frameworks
• Context & Memory Management
• Document Intelligence Layer
• AI Observability & Monitoring Frameworks
• Governance & Responsible AI Controls
• Mentor engineering teams and serve as a thought leader for ent erprise Agentic AI strategy and platform evolution.
• Provide clear portfolio reporting on delivery, financial position, risks, resource constraints, outcomes, and required actions.
• Coordinate across program, finance, technology, business, risk, control, and vendor teams to validate data and resolve issues.
• Drive initiative prioritization and trade-off recommendations based on strategic value, funding, capacity, risk, and readiness.
• Standardize portfolio practices and prepare concise executive dashboards, presentations, and briefing materials.