Senior AI Architect

Programmers.io; Dallas (TX); On-site; USD 180,000 - 260,000; Full time

Job summary

Programmers.io is seeking a Senior AI Architect in Dallas, onsite, to own end-to-end architecture for enterprise AI initiatives. You will design scalable data/model pipelines, integrating GenAI/agentic systems and traditional ML, while guiding delivery teams and client leadership.

You will work across ML lifecycle, from data to deployment, with a focus on performance, security, and cost, mentoring engineers and shaping technical standards.

Qualifications

• 12+ years in software/data engineering or solution architecture, incl. 5+ 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; 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; prompt and context engineering; fine-tuning; evaluation and guardrails.

Responsibilities

• Own end-to-end architecture for enterprise AI systems, spanning data, model, retrieval/orchestration, serving, and integration.
• Architect across traditional ML and GenAI/agentic systems, selecting techniques per problem.
• Design and build frameworks for AI-driven SDLC with guardrails and human-in-the-loop controls.
• Define MLOps/LLMOps practice: CI/CD for models and prompts, registries and versioning, drift and quality monitoring.
• 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 present architecture to engineering and executive audiences.

Skills

AI/ML

GenAI/LLM

MLOps

Cloud platforms

Python

System design

Communication

Education

Bachelor's in Computer Science/Engineering/Data Science

Master's or PhD preferred

Tools

LangChain

LangGraph

LlamaIndex

pgvector

Pinecone

LoRA/QLoRA/PEFT

Job description

One of our leading client is looking for Senior AI Architect in Dallas TX(Onsite)

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.
• Bachelor's in Computer Science, Engineering, Data Science, or related; Master's or PhD preferred. Equivalent demonstrated experience considered.