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
• PTO