What are the responsibilities and job description for the Artificial Intelligence Engineer position at TechnoSphere, Inc.?
Job Role: AI Strategist/Architect (AWS AI Expert)
Location: Miami, Fl Onsite
Job Description for AI Architect (Onsite):
Key job responsibilities
Build and maintain technical trusted advisor relationships with influential technical decision-makers to drive successful adoption and deployment of AWS/GCP services, with particular focus on enterprise-grade AI/ML architectures, Generative AI solutions, and autonomous agent systems.
Architect scalable, secure, and cost-effective solutions leveraging AWS/GCP comprehensive AI services, working with our customers to deeply understand their business needs and to design a technical solution that takes best advantage of the AWS/GCP Cloud platform and Gen AI Services / ML Services.
Serve as a thought leader in the AI/ML space by developing compelling technical content and practical implementations showcasing modern AI architectures. Create reference architectures, workshops, and demos that highlight integration patterns for LLMs, RAG systems, autonomous agents, and MLOps best practices.
Build and nurture an internal AI/ML experts, focusing on knowledge-sharing across traditional ML, Generative AI, and Agentic AI domains. Establish best practices for emerging technologies.
Collaborate across teams to accelerate customer success with AI/ML implementations. Work with business development, professional services, and support teams to ensure effective adoption of AWS/GCP AI services, from proof-of-concept to production deployment.
Drive technical excellence as a key member of the Data and AI Specialist team. Act as a technical liaison between customers and engineering teams, ensuring successful implementation of AI solutions while maintaining alignment with AWS/GCP well-architected framework and AI best practices.
Basic Qualifications
Bachelor's degree in computer science, engineering, mathematics or equivalent
Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
10 years of combined experience in AI/ML and related technologies, with deep expertise in traditional machine learning and deep learning. Must have experience building production-grade AI systems, complemented by practical knowledge of modern Generative AI technologies (LLMs, foundation models, RAG systems) and autonomous agent frameworks.
Strong background in AI architecture patterns and MLOps practices, with demonstrated ability to design and deploy enterprise-grade AI solutions at scale.
Deep experience in design/implementation/consulting experience of Machine Learning/AI/Deep Learning/Gen AI solutions
Strong understanding and experience in the field of AI and related technologies, including deep learning and overall machine learning concepts. Deep experience developing AI models in real-world environments.
Strong understanding of Gen AI technologies. Having worked with both structured and unstructured data in the past to gain effective insights.
Solid grounding in statistics, probability theory, data modelling, machine learning algorithms and software development techniques and languages used to implement analytics solutions
Preferred Qualifications
History of successful technical consulting and/or architecture engagements with large-scale customers or enterprises. Experience migrating or transforming legacy customer solutions to the cloud. Familiarity with common enterprise services.
Presentation skills with a high degree of comfort speaking with executives, IT Management, and developers. Strong written communication skills.
Cloud Technology Certification (such as Solutions Architecture, Cloud Security Professional or Cloud DevOps Engineering)
Master’s degree in computer science, Machine Learning, or related field, with research or practical experience in emerging AI technologies. Published work or significant contributions to AI/ML projects, particularly in Generative AI or autonomous systems, would be highly valued.