REQUIREMENTS:
- 5+ years of experience in Python development, with a strong focus on backend and system design.
- Proficient with Python frameworks like Flask, Django or FastAPI.
- Hands-on experience with containerization technologies such as Docker, and orchestration tools like Kubernetes.
- Experience with cloud platforms (AWS, GCP, or Azure).
- Familiarity with CI/CD pipelines for deploying Python services in production.
- Strong experience with asynchronous programming using Python (e.g., asyncio, aiohttp).
- Experience using task queues like Celery or other distributed task management tools.
- Expertise in SQL, with a focus on performance optimization and data storage strategies.
- Proficient in pytest for unit and integration testing.
- Extensive experience with refactoring legacy code for improved performance and maintainability.
- Experience working with document formats like PDFs, images, and various structured/unstructured data formats.
- Understanding of data structures, algorithms, and best practices for clean, efficient code.
CONSIDERED AS ADVANTAGE:
- Experience with Machine Learning concepts and practical experience with ML frameworks like scikit-learn, XGBoost, PyTorch, or TensorFlow.
- Knowledge of Natural Language Processing (NLP), specifically around document parsing and text extraction (e.g., spaCy, NLTK, or transformers).
- Experience in building or maintaining ML/ETL pipelines using tools like Airflow or MLFlow.
- Prior experience with MLOps practices for deploying machine learning models at scale.
- Experience with Large Language Models (LLMs) and applications such as Retrieval-Augmented Generation (RAG) for document or text-based workflows.
- Data analysis skills, with experience in building analytical tools or services to extract insights from document datasets.
RESPONSIBILITIES:
- Develop, maintain, and optimize a scalable platform for automated document processing.
- Enhance data preprocessing pipelines and text extraction modules.
- Refactor legacy code to improve maintainability, performance, and scalability.
- Implement asynchronous programming techniques to improve system performance.
- Ensure code quality, test coverage, and maintainability through unit testing, integration testing, and code reviews.
- Debug, troubleshoot, and fix issues in both development and production environments.
- Participate in architecture and design discussions to improve the platform’s scalability and performance.
Top Skills
What We Do
We specialize in transforming Revenue Operations through advanced technological integration, combining AI, analytics, and strategic workflow automation.
Our core competency lies in developing comprehensive revenue optimization strategies that unify critical business functions including marketing, sales, billing, enterprise resource planning, and revenue recognition.
Leveraging SAP and other vendors' enterprise technologies we deliver sophisticated solutions that enable organizations to:
- Develop strategic outcome-based business models
- Implement enterprise-wide digital transformation
- Optimize complex revenue management processes
- Minimize implementation risks and operational costs
Our approach is distinguished by:
1. Comprehensive industry expertise
2. Advanced technological architecture
3. Proven deployment methodologies
4. Balanced focus on long-term strategic planning and immediate operational improvements
We collaborate with clients to design precision-engineered revenue ecosystems that align technological capabilities with strategic business objectives, ensuring sustainable growth and operational efficiency.
Expertise Areas:
1. Intelligent Revenue Operations (iRevOps)
2. Enterprise Technology Integration
3. Strategic Digital Monetization
4. AI-Enhanced Business Process Optimization
Our methodological framework transforms complex business requirements into streamlined, data-driven operational strategies.
