Job Summary

This role is responsible for leading the architectural design and implementation of advanced AI and machine learning solutions, ensuring scalability, reliability, and alignment with industry best practices. The position drives strategic technology initiatives, oversees governance and compliance, and fosters innovation through technical leadership and thought contribution. The individual will leverage deep expertise in AI/ML frameworks, distributed systems, and data engineering to deliver enterprise-grade solutions that address complex business challenges.

Key Responsibilities

1. Architect scalable AI/ML solutions using Python, TensorFlow, PyTorch, and Spark Mllib, ensuring robust model development and integration with distributed data platforms.
2. Design and optimize machine learning pipelines leveraging Apache Spark, Kafka, and Airflow to enable efficient data ingestion, processing, and real-time analytics.
3. Implement advanced data models and storage solutions using PostgreSQL and MySQL, supporting high-volume, low-latency data requirements for AI-driven applications.
4. Establish and enforce architectural governance by reviewing solution designs and ensuring compliance with industry standards, security protocols, and organizational policies.
5. Drive innovation by researching emerging AI/ML technologies, submitting whitepapers, participating in industry forums, and contributing to patent filings.
6. Mentor and train team members in AI/ML methodologies, Python programming, and best practices for scalable solution delivery, ensuring technical capability and risk mitigation.
7. Collaborate with stakeholders to translate business requirements into technical specifications, crafting solutions that align with strategic objectives and domain expertise.
8. Oversee the adoption of classical machine learning, deep learning, NLP, and time series forecasting techniques, ensuring solutions remain current and competitive.
9. Architect and implement RESTful API integrations to enable seamless communication between AI/ML components and external systems, ensuring scalable, secure, and efficient data exchange across diverse enterprise environments.

Skill Requirements

1. Architectural Leadership In Ai/Ml Solution Design, With Expert Proficiency In Python, Machine Learning Model Development, And Distributed Data Engineering.
2. Excellent Knowledge Of Deep Learning Frameworks Such As Tensorflow, Pytorch, And Scikitlearn.
3. Advanced Proficiency In Building And Optimizing Data Pipelines Using Apache Spark, Kafka, And Airflow.
4. Solid Experience With Relational Databases Including Postgresql And Mysql, And Data Manipulation Using Pandas And Numpy.
5. Expertise In Classical Ml, Deep Learning, Nlp, And Time Series Forecasting.
6. Strong Understanding Of Cloudbased Platforms And Scalable Infrastructure (E.G., Databricks).
7. Excellent Skills In Technical Governance, Compliance, And Architectural Best Practices.

Agentic AI, LangChain, LangGraph, Retrieval-Augmented Generation (RAG), Large Language Modeling, Vector Databases

Other Requirements

1. Recommended certifications: TensorFlow Developer Certificate
2. AWS Certified Machine Learning � Specialty,
3. Databricks Certified Data Enginee