AI Solutions Architect

Overview

Remote
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 12 month(s)
No Travel Required

Skills

AWS
Python
Java
GCP
azure
AI
R

Job Details


The AI Solution Architect will be responsible for translating complex business challenges into viable, scalable, and secure AI/ML solutions. This role requires a deep understanding of AI/ML methodologies, data architectures, cloud platforms, and software engineering best practices. The successful candidate will work closely with business stakeholders, data scientists, ML engineers, software developers, and IT operations teams to architect, guide, and ensure the successful delivery of AI-powered products and services.

Required Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related quantitative field.

[5+] years of experience in solution architecture, with at least [10+] years specifically focused on designing and implementing AI/ML solutions in an enterprise environment.

Proven expertise in designing and deploying end-to-end machine learning pipelines. Strong understanding of various AI/ML techniques and algorithms (e.g., supervised, unsupervised, reinforcement learning, deep learning, NLP, computer vision).

Hands-on experience with at least one major cloud platform's AI/ML services (AWS, Azure, Google Cloud Platform).

Proficiency in programming languages commonly used in AI/ML (e.g., Python, R, Java).

Familiarity with MLOps principles and tools for continuous integration, deployment, and monitoring of ML models.

Solid understanding of data governance, data quality, and data security principles. Excellent problem-solving, analytical, and critical thinking skills.

Strong communication, presentation, and interpersonal skills, with the ability to influence and collaborate effectively across diverse teams. Preferred Qualifications: Experience with Generative AI models (LLMs, diffusion models) and related frameworks (e.g., LangChain, LlamaIndex).

Experience with big data technologies (e.g., Spark, Hadoop, Kafka). Certifications in relevant cloud AI/ML platforms (e.g., AWS Certified Machine Learning Specialty, Google Cloud Professional Machine Learning Engineer).

Experience with agile development methodologies

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