Cloud Architect

AI Cloud Solutions Architect 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 AI System Design & Strategy Technical Execution Influence and Leadership Execution and Delivery 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

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