Cloud Architect
Location: Dallas, TX
Employment Type: Direct Hire
Job ID: 141011
Date Added: 06/30/2026
Location: Addison, TX – Onsite 4 days a week
The Company
Headquartered in Dallas TX, our client is a technology and strategy consultancy that aims to provide a competitive edge for its clients by solving complex problems with data, software, and strategy. They specialize in areas like technology strategy, product development, software engineering, and digital transformation, with a particular emphasis on AI, MLOps, and Data Engineering. The firm's clientele spans various industries, including AgTech, Healthcare, Logistics, and Financial Services.
Platform / Stack
You will work with technologies that include Azure, Terraform, Python, and MLOps.
Compensation Expectation: $170,000 – $175,000
What You'll Do As a AI Cloud Solutions Architect:
- AI System Design & Strategy
- Architect end-to-end AI solutions — from data ingestion and feature engineering through model training, evaluation, deployment, and monitoring.
- Evaluate and select appropriate AI approaches for client problems: supervised learning, LLMs, RAG, agentic systems, computer vision, NLP, and time-series forecasting.
- Technical Execution
- Design and oversee the build of AI/ML infrastructure: model serving layers, vector stores, embedding pipelines, orchestration frameworks, and feedback loops.
- Lead technical reviews of model performance, data quality, prompt engineering, fine-tuning approaches, and inference optimization.
- Influence and Leadership
- Act as a trusted AI advisor to client executives and engineering teams — translating AI capabilities into business outcomes and setting realistic expectations.
- Build alignment across data, cloud, and application teams to ensure AI systems are well-integrated and operationally sound.
- Execution and Delivery
- Translate AI architecture decisions into clear implementation roadmaps, sprint plans, and measurable success criteria.
- Ensure AI systems meet governance standards: model cards, bias assessments, data lineage, version control, and audit trails.
Qualifications:
You could be a great fit if you have:
- 8+ years in software engineering, data science, or ML engineering; 3+ years in a dedicated AI/ML architecture or technical lead role.
- Proven experience designing and deploying production AI/ML systems on cloud platforms (AWS, Azure, or GCP), including model serving, pipelines, and monitoring.
- Strong command of modern AI/ML tooling: Python, PyTorch or TensorFlow, Hugging Face, LangChain or LlamaIndex, and vector databases (Pinecone, Weaviate, pgvector).
- Hands-on experience with LLM integration patterns: RAG, prompt engineering, fine-tuning, function calling, and multi-agent orchestration.
- Solid understanding of MLOps practices: experiment tracking (MLflow, W&B), CI/CD for models, model registries, drift detection, and A/B evaluation frameworks.
- Exceptional communication skills — able to explain AI system trade-offs clearly to both engineers and non-technical stakeholders.
- Preferred
- Experience deploying AI in regulated or operationally complex industries such as financial services, agriculture, logistics, or construction.
- Familiarity with responsible AI frameworks: fairness, explainability (SHAP, LIME), privacy-preserving techniques, and model risk management.
- Exposure to edge AI, IoT sensor data, or real-time inference at scale.
- Understanding of data architecture fundamentals: feature stores, data lakes, streaming pipelines, and the data contracts that underpin reliable AI.
- Professional certifications (e.g., AWS Certified ML Specialty, Google Professional ML Engineer, Azure AI Engineer Associate, Deep Learning Specialization).
Benefits Offered:
Employer provides access to:
- Medical, Vision, & Dental benefits
- 401k
- PTO