Senior AI Architect

Senior AI Architect Dallas, TX (On-site) Full-time AI Center of Excellence • ~25% travel About the role Programmers.io delivers production AI systems for clients across financial services, insurance, retail, and manufacturing — spanning traditional machine learning, generative AI, and agentic systems, plus the frameworks that let us deliver them at speed and with engineering rigor. We are expanding our architecture team with a senior, full-stack AI Architect in Dallas. You will own solution and technical architecture end to end, build reusable frameworks — including frameworks for AI-driven software development — and stay hands-on through delivery, while partnering with client leadership on the technical direction of major AI initiatives. Genuine depth across both classical AI/ML and modern GenAI/agentic systems is essential. Responsibilities Own end-to-end architecture for enterprise AI systems, spanning data, model, retrieval/orchestration, serving, and integration, designed for scale, performance, security, cost, and reliability. Architect across the full spectrum: traditional ML and deep learning (statistical modeling, forecasting, NLP, computer vision, full model lifecycle) and GenAI/agentic systems (LLMs, RAG, multi-agent orchestration, fine-tuning), choosing the right technique for each problem. Design and build complete frameworks for AI-driven SDLC — spec-driven development, code generation, migration/modernization, test generation, review, and documentation — with the orchestration, guardrails, and human-in-the-loop controls that make agentic delivery enterprise-safe. Define MLOps/LLMOps practice: CI/CD for models and prompts, registries and versioning, drift and quality monitoring, evaluation, and scalable, cost-optimized inference. Embed responsible-AI, security, data-governance, and model-risk considerations into architectures from the start. Partner with sales and client executives to shape solutions, scope proposals and RFP responses, and present architecture to engineering and executive audiences; provide design direction and mentorship to distributed delivery teams. Required qualifications Experience: 12+ years in software/data engineering or solution architecture, including 5+ in AI/ML and 2+ hands-on with production GenAI/LLM systems; at least three enterprise AI systems delivered to production. Traditional AI/ML: statistics and ML fundamentals; classical algorithms and deep learning (transformers, CNNs/RNNs); feature engineering; model training, evaluation, deployment, and monitoring. Generative AI/LLM: LLMs (GPT, Claude, Gemini, Llama, Mistral); RAG and retrieval design; embeddings and vector databases (e.g., pgvector, Pinecone); prompt and context engineering; fine-tuning (LoRA/QLoRA/PEFT); evaluation and guardrails. Agentic systems: multi-agent orchestration, tool use, memory/state; frameworks such as LangChain/LangGraph, LlamaIndex, or equivalents; and MCP. AI-driven SDLC: hands-on applying AI across the lifecycle and building frameworks/accelerators — not just using tools. Cloud & platforms: strong on at least one of AWS (Bedrock, SageMaker), Azure (Azure OpenAI, Azure ML), GCP (Vertex AI); cloud-native, distributed, event-driven design. Engineering: expert Python; API and microservices design; Docker/Kubernetes; CI/CD; SQL/NoSQL and graph/knowledge graphs; strong design-patterns and system-design grounding. Non-functional rigor: scalability, performance, security, observability, and cost at enterprise scale. Communication: credible with CIOs and engineers alike; experience mentoring and setting technical standards. Preferred qualifications Regulated or high-complexity enterprise experience (financial services, insurance, retail, manufacturing). AI-based legacy modernization and code transformation. AI governance / model-risk frameworks in practice (e.g., SR 11-7, NIST AI RMF, ISO/IEC 42001). Building frameworks, platforms, or accelerators adopted across multiple teams or clients. Consulting or systems-integration background. Education & details Bachelor's in Computer Science, Engineering, Data Science, or related; Master's or PhD preferred. Equivalent demonstrated experience considered. On-site, Dallas, TX; ~25% travel. Full-time. Visa sponsorship is not available for this position; applicants must already be authorized to work in the United States on a permanent basis. Show more Show less