AI Architect
randomtreesCorpus Christi (TX)
About the role
Communication: Excellent verbal and written communication, with the ability to explain complex concepts simply and influence decisions. Architecture: Proven experience designing complex, distributed AI/ML systems and platforms end to end. AI/ML expertise: Strong grounding in machine learning, deep learning, and (ideally) GenAI/LLMs, including RAG and fine-tuning. MLOps: Hands-on experience with tools such as MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, Azure ML, or Databricks. Engineering: Strong programming skills (Python required), plus experience with Docker, Kubernetes, and microservices/API design. Cloud and data: Experience with AWS, Azure, or GCP, and with big data technologies (Spark, Kafka, data lakes/warehouses).Stakeholder management: A track record of working with senior stakeholders, managing expectations, and delivering across teams. Resilience: Comfortable with ambiguity, tight timelines, and challenging technical environments.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
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