Data & AI Solutions Architect

Sphere Software; United States; Remote; USD 150,000 - 200,000; Full time

Job summary

Sphere Software is seeking an AI Solutions Architect to design and implement Generative AI solutions. The role focuses on building LLM-based agents, deploying ML models, and translating research into practical, client-ready applications.

You will work with cross-functional teams to integrate AI into existing workflows, stay ahead of AI trends, and lead training programs to develop technical expertise across the organization.

Qualifications

• At least 3 years of experience creating AI solutions using Databricks (certification a plus).
• Experience with generative AI frameworks such as Langchain and LlamaIndex.
• Familiarity with OpenAI, Google, or open-source NLP/LLM models (e.g., Llama, Claude, Hugging Face).
• Minimum 5 years of Python and SQL programming experience.
• Proficiency with diverse data storage systems (RDBMS, NoSQL).
• Experience with major cloud platforms, especially GCP (2–3+ years) and AWS knowledge.
• Understanding of neural networks (GANs, Transformers).
• Experience with TensorFlow, PyTorch, and Keras for model design and validation.
• Familiarity with MLOps CI/CD and IaC (Biceps, Terraform).
• Data preprocessing and feature engineering for AI models.
• Knowledge of ML/data pipelines and training/serving methodologies.
• Deploying ML models using Databricks or other MLOps platforms.
• Understanding of NLP/LLM domains and applications.
• Proactive, innovative mindset and risk awareness.
• Excellent communication and presentation skills.

Responsibilities

• Develop Generative AI solutions using GCP services across client teams.
• Contribute to development and application of LLMs and Generative AI.
• Translate research into practical AI applications.
• Explain complex technical concepts to non-technical stakeholders.
• Collaborate with cross-functional teams to integrate AI into existing workflows.
• Stay updated on advancements in generative AI technologies.
• Optimize and fine-tune generative models for performance and efficiency.
• Troubleshoot issues related to generative AI models.
• Create and maintain documentation for AI models and applications.
• Deploy and monitor ML models with a focus on generative AI and LLM-based agents.
• Design prototypes with IT practitioners and client stakeholders.
• Evaluate new tools/tech for efficient deliverables.
• Demonstrate confidence in ambiguity and influence business decisions with trade-offs.
• Engage in continuous learning about capabilities, limitations, and applications of AI stacks.
• Assist leadership in building/upgrading architectures and service lines.
• Lead training programs to build technical expertise.

Skills

Python

SQL

GCP

LLMs

MLOps

CI/CD

Data preprocessing

NLP

Communication

Tools

Databricks

Langchain

LlamaIndex

TensorFlow

PyTorch

Keras

Terraform

Biceps

Job description

Sphere combine global expertise and local insight to help people and companies to turn their ambitious goals into reality. At Sphere we put people first and strive to be a changemaker by building a better future through innovation and technology.

Now we are looking for an AI Solutions Architect to join our team and help our customers to improve their service.

Location: Remotely
Type: Contract
Start Date: ASAP

Responsibilities

• Develop Generative AI solutions utilizing GCP services, across various client teams;
• Contribute to the development and application of Large Language Models (LLMs) and Generative AI;
• Explore new areas within LLMs and Generative AI, translating research into practical applications;
• Communicate complex technical concepts and findings to non-technical stakeholders;
• Collaborate with cross-functional teams to integrate generative AI solutions into existing workflow systems;
• Stay updated on the latest advancements in generative AI technologies and methodologies;
• Optimize and fine-tune generative models for performance and efficiency;
• Troubleshoot and resolve issues related to generative AI models and implementations;
• Create and maintain documentation for generative AI models and their applications;
• Deploy and monitor Machine Learning models, focusing on generative AI and LLM-based agents;
• Design and develop prototypes in collaboration with IT practitioners and client stakeholders;
• Evaluate new tools and technologies, selecting appropriate ones for efficient and quality deliverables;
• Demonstrate confidence and ability to work in ambiguous situations;
• Influence business decisions by providing recommendations and trade-offs;
• Engage in continuous research and learning to attain in-depth knowledge of capabilities, limitations, internal architecture, and applications of a broad range of trending tech stacks, presenting essential comparisons, pros/cons, and target use cases;
• Assist leadership in building or upgrading reference architectures, developing new service lines or enhancing existing ones, and designing and implementing programs to align delivery teams with new or enhanced service offerings;
• Lead training programs to help the next generation gain technical expertise.

Requirements

• At least 3 years of experience in creating AI solutions using Databricks (certification is a plus);
• Experience with generative AI frameworks, such as LlamaIndex and Langchain;
• Familiarity with generative AI models from OpenAI, Google, or open-source alternatives (e.g., Llama, Claude, Hugging Face);
• Minimum of 5 years of programming experience in Python and SQL;
• Proficiency in diverse data storage systems, including RDMS and NoSQL;
• Expertise in utilizing major cloud platforms, with a strong emphasis on GCP (minimum 2-3 years of experience) and knowledge of AWS;
• Understanding of neural network architectures, such as Generative Adversarial Networks (GANs) and Transformers;
• Experience using TensorFlow, PyTorch, and Keras for designing, training, and validating AI models;
• Familiarity with CI/CD solutions in the context of MLOps and LLMOps, including automation with Infrastructure as Code (IaC) tools like Biceps or Terraform;
• Skills in data preprocessing and feature engineering for AI model training;
• Knowledge of designing and explaining data pipelines, ML pipelines, and ML training and serving methodologies;
• Experience in deploying ML models using native infrastructure (e.g., Databricks) or third-party MLOps platforms;
• Understanding of specific domains or industries and the application of NLP/LLM solutions;
• Demonstrated innovative mindset and problem-solving abilities;
• Awareness of AI standards and the ability to assess and mitigate technology risks;
• Excellent communication and presentation skills.

Sphere offers a competitive and rewarding salary and benefits package, as well as an intellectually and creatively stimulating work environment, flexibility, and unique international travel opportunities.