AI Solutions Architect

AI Solutions Architect

• Design and implement

  Generative AI solutions

  leveraging AWS services such as S3, Redshift, and Snowflake.
• Contribute to the development, fine-tuning, and application of

  Large Language Models (LLMs)

  and Generative AI frameworks.
• Explore and apply emerging advancements in LLMs and generative AI to practical client use cases.
• Communicate complex technical concepts and insights effectively to non-technical stakeholders.
• Collaborate with cross-functional teams to integrate AI solutions into existing workflows and platforms.
• Optimize and fine-tune generative models for scalability, efficiency, and performance.
• Troubleshoot, monitor, and maintain deployed AI/ML models.
• Develop prototypes in partnership with IT practitioners and client stakeholders.
• Evaluate and recommend tools, frameworks, and technologies to ensure efficient delivery of high-quality solutions.
• Support leadership with building/upgrading reference architectures and enhancing service offerings.
• Lead training initiatives to mentor teams and develop next-generation technical expertise.

• 3+ years

  of experience in building AI solutions with

  Databricks

  (certification preferred).
• Experience with

  Generative AI frameworks

  (e.g., LlamaIndex, LangChain).
• Familiarity with

  AI models from OpenAI, Google, or open-source alternatives

  (Llama, Claude, Hugging Face).

• 5+ years of programming experience

  with Python and SQL.
• Strong knowledge of

  data storage systems

  (RDBMS, NoSQL).
• Expertise in AWS (minimum 2 3 years); exposure to

  Azure

  is a plus.
• Solid understanding of

  neural network architectures

  (GANs, Transformers).
• Experience with

  TensorFlow, PyTorch, and Keras

  for model design, training, and validation.
• Familiarity with

  MLOps/LLMOps pipelines

  , CI/CD solutions, and IaC tools (Terraform, Biceps).
• Strong background in

  data preprocessing and feature engineering

  .
• Hands-on experience deploying ML models using native or third-party MLOps platforms.
• Knowledge of

  NLP/LLM applications

  in specific domains or industries.
• Strong communication, problem-solving, and presentation skills.

• Experience designing

  end-to-end ML/AI pipelines

  for enterprise-scale systems.
• Familiarity with

  AI standards and compliance frameworks

  .
• Proven ability to work in

  ambiguous or fast-changing environments

  .
• Experience influencing business decisions through data-driven AI recommendations.