AI Architect

CTP Consulting

  • Dallas, TX
  • 1 day ago
  • $150,000–$175,000 Per Year
  • Full-time

Highlights

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.

Numbers & Facts

LocationDallas, TX
Job TypeFull-time
Salary$150,000–$175,000 Per Year
Company Size51 - 200
Year Founded2010
HeadquartersSan Luis Obispo, CA, US
Additional CompensationBonus
Websitehttps://ctpconsulting.com/

Description

Job Title: AI Cloud Solutions Architect
Location: Addison, TX – Onsite 4 days a week
Compensation Expectation: $150,000 – $175,000

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.

Job Responsibilities

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

Paid Time-Off, Professional Development, 401K, Medical, Dental, Vision

About Company

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.

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