DEVELOPER (Senior Software Engineer) - Data Analyst

Responsibilities
1. RAG Architecture & Pipeline Design
§ Design and maintain RAG that connects CRM to LLM to provide grounded, fact bases AI responses.
2. Vector Search & NLP
§ Implement and maintain vector embeddings for entities to enable semantic search and integration with LLM for generative AI features.
3. MCP Server Development
§ Design and deploy MCP to bridge LLM with existing Data sources for real-time Retrieval.
4. Generative AI Integration
§ Utilize LLMs to synthesize retrieved data into accurate, user friendly natural language responses.
5. Performance Optimization
§ Evaluate and optimize the end-to-end latency of search and generation.
6. Data Analysis
§ Collect, analyze, and interpret large datasets to identify trends, patterns, and insights that can inform business decisions.
7. Technical Leadership
§ Lead code reviews, ensuring adherence to coding standards, best practices, and quality requirements.
§ Act as a technical point of contact for complex database issues, offering solutions and recommendations to resolve them.
8. Project Coordination and Stakeholder Collaboration
§ Collaborate with project managers, business analysts, and stakeholders to understand business requirements and translate them into technical solutions.
9. Quality Assurance and testing
§ Collaborate with QA teams to validate data quality, ensure accuracy, and troubleshoot issues identified during testing.
10. Continuous Improvement
§ Stay up-to on the latest tools, techniques, and best practices.
§ Identify opportunities for process improvements, optimizations, and automation.
11. Documentation and Standards
§ Ensure adherence to data governance and regulatory requirements, including security and compliance standards.
Contributing Responsibilities
§ Design, develop, implement and maintain AI/LLM products to solve specific business use cases.
§ Implement and maintain vector embeddings for entities to enable semantic search and integration with LLM for generative AI features.
§ Design and deploy MCP to bridge LLM with existing Data sources for real-time Retrieval.
§ Design and maintain RAG that connects CRM to LLM to provide grounded, fact bases AI responses.
§ Explore and understand the CRM data, including customer demographics, behavior, and transactional data.
§ Develop and train predictive models using various machine learning algorithms and techniques.
§ Deploy models in production environments, such as CRM systems.
§ Monitor model performance, identify areas for improvement, and retrain models as necessary.
§ Generate insights and recommendations based on data analysis and modeling results.
§ Communicate insights and results to stakeholders, including business leaders.
§ Identify opportunities to improve CRM data quality, processes, and systems.
§ Collaborate with project managers, business analysts, and stakeholders to understand business requirements and translate them into technical solutions.
§ Stay current with industry trends, new technologies, and emerging methodologies in data science and CRM.
§ Excellent Communication and Listening Skills, attention to details is must