Principal Solution Architect

We are seeking a highly skilled and experienced Principal AI Solution Architect to join our dynamic team. The candidate will lead the AI Solutioning and Designing across Enterprise Teams and cross-functional teams.

They will primarily be working with the MDM CoE to lead and drive AI solutions and optimizations and also provide thought leadership. The role involves developing and implementing AI strategies, collaborating with cross-functional teams, and ensuring the scalability, reliability, and performance of AI solutions. To succeed in this role, the candidate must have strong AI/ML, Data Science , GenAI experience along with MDM knowledg .

Candidate must have AI/ML, data science and GenAI experience on technologies like ( PySpark / PyTorch , TensorFlow, LLM , Autogen , Hugging FaceVectorDB , Embeddings, RAGs etc ), along with knowledge of MDM (Master Data Management)

Roles & Responsibilities:

• Lead the Designing, solutioning and development of enterprise-level GenAI applications using LLM frameworks such as Langchain , Autogen , and Hugging Face.

• Architect intelligent pipelines using PySpark , TensorFlow, and PyTorch within Databricks and AWS environments.

• Implement embedding models and manage VectorStores for retrieval-augmented generation (RAG) solutions.

• Integrate and leverage MDM platforms like Informatica and Reltio to supply high-quality structured data to ML systems.

• Utilize SQL and Python for data engineering, data wrangling, and pipeline automation.

• Build scalable APIs and services to serve GenAI models in production.

• Lead cross-functional collaboration with data scientists, engineers, and product teams to scope, design, and deploy AI-powered systems.

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

Basic Qualifications and Experience:

• Masters degree with years of experience in Data Science, Artificial Intelligence, Computer Science, or related fields OR

• Bachelors degree with years of experience in Data Science, Artificial Intelligence, Computer Science, or related fields OR

• Diploma with years of hands-on experience in Data Science, AI/ML technologies, or related technical domains

Functional Skills :

Must-Have Skills:

• 1 4 + years of experience working in AI/ML or Data Science roles, including designing and implementing GenAI solutions.

• Extensive hands-on experience with LLM frameworks and tools such as Langchain , Autogen , Hugging Face, OpenAI APIs, and embedding models.

• Expertise in AI/ML solution architecture and design , knowledge of industry best practices

• Experience desining GenAI based solutions using Databricks platform

• Hands-on experience with Python, PySpark , PyTorch , LLMs, Vector DB, Embeddings, SciKit , Langchain , SK-learn, Tensorflow , APIs, Autogen , VectorStores , MongoDB, DataBricks , Django

• Strong knowledge of AWS and cloud-based AI infrastructure

• Excellent problem-solving skills

• Strong communication and leadership skills

• Ability to collaborate effectively with cross-functional teams and stakeholders

• Experience in managing and mentoring junior team members

• Must be able to p rovide thought leadership to the junior team members

Good-to-Have Skills:

• Prior experience in Data Modeling, ETL development, and data profiling to support AI/ML workflows.

• Working knowledge of Life Sciences or Pharma industry standards and regulatory considerations.

• Proficiency in tools like JIRA and Confluence for Agile delivery and project collaboration.

• Familiarity with MongoDB, VectorStores , and modern architecture principles for scalable GenAI applications.

Professional Certifications :

• Any Data Analysis certification (SQL , Python, Other DBs or Programming languages )

• Any cloud certification (AWS or AZURE)

• Data Science and ML Certification s

Soft Skills:

• Strong analytical abilities to assess and improve master data processes and solutions.

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

• Effective problem-solving skills to address data-related issues and implement scalable solutions.

• Ability to work effectively with global, virtual teams