Enterprise AI Architect - GenAI, MLOps & Scalable Systems

Programmers.io; Dallas (TX); On-site; USD 190,000 - 230,000; Full time

Job summary

Programmers.io is seeking a senior AI/ML solutions architect to own the end-to-end architecture of enterprise AI systems, spanning data, models, retrieval/orchestration, serving, and integration. You will design frameworks for AI-driven SDLC with guardrails and human-in-the-loop controls, and lead architecture discussions with CIOs and engineers.

The role requires deep experience across traditional ML, NLP, vision, and GenAI/agentic systems, plus strong cloud and system-design skills to deliver

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.
• Strong Python, API design, Docker/Kubernetes, CI/CD fundamentals.
• Experience with LLMs, RAG, embeddings, and prompts engineering.
• Cloud platform experience across AWS/Azure/GCP.

Responsibilities

• Own end-to-end architecture for enterprise AI systems across data, model, retrieval, and serving.
• Architect traditional ML, DL, and GenAI/agentic systems; select appropriate techniques.
• Build AI-driven SDLC frameworks with guardrails and human-in-the-loop controls.
• Define MLOps/LLMOps practices including CI/CD for models and prompts.
• Embed responsible AI, security, data governance and model risk from the start.
• Collaborate with sales and executives to shape solutions and guide delivery teams.

Skills

Python

API design

Docker

Kubernetes

CI/CD

MLOps

System design

Cloud platforms

LangChain

LlamaIndex

Tools

pgvector

Pinecone

LangChain

LlamaIndex

Job description

Programmers.io is seeking a senior AI/ML solutions architect to own the end-to-end architecture of enterprise AI systems, spanning data, models, retrieval/orchestration, serving, and integration. You will design frameworks for AI-driven SDLC with guardrails and human-in-the-loop controls, and lead architecture discussions with CIOs and engineers.

The role requires deep experience across traditional ML, NLP, vision, and GenAI/agentic systems, plus strong cloud and system-design skills to deliver