Principal Solution Architect - AI

Principal AI Solution Architect

Roles & Responsibilities

• AI Architecture & Solutioning:

  Lead the design and development of enterprise-level

  GenAI

  applications using frameworks like

  Langchain, Autogen

  , and

  Hugging Face

  . You will architect intelligent data pipelines using

  PySpark, TensorFlow

  , and

  PyTorch

  within

  Databricks

  and

  AWS

  environments.

• Data Integration & Engineering:

  Integrate and leverage

  MDM

  platforms like

  Informatica

  and

  Reltio

  to supply high-quality structured data to

  ML

  systems. You will utilize

  SQL

  and

  Python

  for data engineering, data wrangling, and pipeline automation.

• GenAI

  Implementation:

  Implement embedding models and manage

  VectorStores

  for

  Retrieval-Augmented Generation (RAG)

  solutions. You will also build scalable

  APIs

  and services to serve

  GenAI

  models in production.

• Leadership & Collaboration:

  Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy

  AI

  -powered systems. You will also provide thought leadership and mentorship to junior team members.

• Governance & Compliance:

  Ensure model governance, version control, and auditability are aligned with regulatory and compliance expectations.

Technical Skills

• Extensive hands-on experience (14+ years) in

  AI/ML

  or Data Science, including designing and implementing

  GenAI

  solutions.
• Expertise in

  AI/ML

  solution architecture and design, with a strong knowledge of industry best practices.
• Hands-on experience with

  Python, PySpark, PyTorch, LLMs, Vector DB, Embeddings, Langchain, Autogen

  , and frameworks like

  TensorFlow

  .
• Experience designing

  GenAI

  -based solutions using the

  Databricks

  platform.
• Strong knowledge of

  AWS

  and cloud-based

  AI

  infrastructure.
• Prior experience in Data Modeling,

  ETL

  development, and data profiling to support

  AI/ML

  workflows is a plus.
• Proficiency in tools like

  JIRA

  and

  Confluence

  for Agile delivery is a plus.

• AWS

  or

  Azure

  certifications, and Data Science and

  ML

  certifications are preferred.

Qualifications

• A Master's degree with 11-14 years of experience, a Bachelor's degree with 15-16 years of experience, or a Diploma with 17-18 years of hands-on experience in Data Science,

  AI/ML

  technologies, or related technical domains.

Soft Skills

• Leadership:

  Strong communication and leadership skills, with a proven ability to manage and mentor junior team members.

• Problem-Solving:

  Excellent problem-solving skills and strong analytical abilities.

• Collaboration:

  The ability to collaborate effectively with cross-functional teams and stakeholders.

• Communication:

  Excellent verbal and written communication skills, with the ability to convey complex data concepts to technical and non-technical stakeholders.