AI Architect

Programmers.io; Dallas (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

Programmers.io is expanding its architecture team in Dallas by hiring a senior, full-stack AI Architect. You will own end-to-end enterprise AI architectures, build reusable AI development frameworks, and stay hands-on through delivery, while partnering with client leadership on technical direction of major AI initiatives.

The role requires deep experience across classic AI/ML and modern GenAI/agentic systems, with a track record delivering multiple enterprise AI projects.

Qualifications

• 12+ years in software/data engineering or solution architecture
• 5+ years in AI/ML and 2+ hands-on with production GenAI/LLM systems
• At least three enterprise AI systems delivered to production
• Experience with traditional AI/ML: statistics, ML fundamentals, transformers, CNNs/RNNs
• Experience with GenAI/LLMs: RAG, embeddings, prompting, fine-tuning
• Experience with multi-agent orchestration and tool use

Responsibilities

• Own end-to-end architecture for enterprise AI systems across data, model, retrieval, serving, and integration
• Architect across traditional ML and deep learning and GenAI/agentic systems
• Design and build frameworks for AI-driven SDLC including code generation and testing
• Define MLOps/LLMOps practices: CI/CD for models, drift monitoring, evaluation
• Embed responsible AI, security, data governance, and model risk
• Mentor delivery teams and shape solutions with client executives

Skills

Python

API design

Docker/Kubernetes

ML/AI fundamentals

System design

Communication

Education

Bachelor's in Computer Science/Engineering/Data Science

Tools

LangChain

LlamaIndex

Pinecone

pgvector

SageMaker

Vertex AI

Job description

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.