Data and AI Engineer

We’re looking for an experienced, motivated hands-on Data and AI engineer who brings ideas about handling largescale enterprise applications leveraging data platforms; As a software engineer, you’ll apply your deep expertise in designing, developing, delivering, and supporting a world class software and data platform. You will take full ownership of delivering high-impact big data platform that is robust, scalable and support production-grade applications and services for the supply chain space. You will leverage open source and cloud storage tools to build and develop reusable components and architecture that can enable the data science teams to provide best in class AI/ML and data analysis environment.

You will also help in providing technical direction and develop strategies for long-term platform growth. You need to be versatile, display leadership qualities and open minded to take on new problems that our customers face.

The day today responsibilities include,

Analyzes and designs reusable components of the data platform and services required to support the data storage, data schema, data orchestration.

Design, develop, troubleshoot, and scale the data pipelines required to support the various analytics and AI/ML workloads.

Understand application produced artifacts, design the entire pipeline of schema definition, efficient storage and query of various entity objects.

Train, fine-tune, evaluate, and optimize AI models for specific use cases, ensuring accuracy, performance, cost-effectiveness, and scalability.

Seamlessly integrate AI models and autonomous agent solutions into cloud-based products to drive smarter workflows and improved productivity

Develop reusable tools, libraries, and components that standardize and accelerate the development of AI solutions across the organization.

Monitor and maintain deployed models, ensuring consistent performance and reliability in production environments

Translate complex technical and functional problems into detailed designs

Partner and work with data scientists in the team in taking data science algorithms and integrating them efficiently for high scale production application.

Provide senior level support and mentoring by evaluating product enhancements for feasibility studies and providing completion time estimates

Develop high quality unit, tests functional tests and integration tests supporting the data extract, transform, load pipelines

Ensure product quality by participating in design reviews, code reviews and working with the team for end-to-end validation of the entire product

Design and develop various data validation strategies ensuring that robust , good quality data is provided to data science teams for model development and advanced analytics

Define data governance, data auditing policy and strategies for compliance and security controls

Write and maintain technical documentation for the various projects. Review product user documentation for technical accuracy and completeness


Required education
Bachelor's Degree

Preferred education
Bachelor's Degree

Required technical and professional expertise

5-7 years of experience in developing enterprise applications using Java, Python, spark and related technologies with 2+ years of focus on DataEngineering, DataOps, MLOps and AI Engineering

- Software development strategies for low latency, high throughput softwares

Hands-on experience with common distributed processing tools and languages Python, Spark, Hive, Presto

Deep understanding of data pipelines, data modeling strategies, schema management

Experience with specialized data architectures like data lake, data mesh and optimizing data layouts for efficient processing.

Hands on Experience with streaming platforms and frameworks like Kafka, spark-streaming

Hand on Experience in integrating AI models into real-world applications

Strong understanding of advanced algorithms used in design and development of enterprise grade software

Familiarity with pipeline orchestrator tools like Argo, Kubeflow, Airflow or other open source

Familiarity with platforms like Kubernetes and experience building on top of the native platforms

Good written and verbal communication skills

Ability to provide guidance to less experienced team members.


Preferred technical and professional experience

Proficiency in Java, Python, Spark, and related technologies

Hands-on experience with common distributed processing tools and languages Python, Spark, Hive, Presto

Familiarity with pipeline orchestrator tools like Argo, Kubeflow, Airflow or other open source

Familiarity with platforms like Kubernetes and experience building on top of the native platforms