Senior Software Engineer

Responsibilities

• RAG Architecture & Pipeline Design

§ Design and maintain RAG that connects CRM to LLM to provide grounded, fact bases AI responses.

• Vector Search & NLP

§ Implement and maintain vector embeddings for entities to enable semantic search and integration with LLM for generative AI features.

• MCP Server Development

§ Design and deploy MCP to bridge LLM with existing Data sources for real-time Retrieval.

• Generative AI Integration

§ Utilize LLMs to synthesize retrieved data into accurate, user friendly natural language responses.

• Performance Optimization

§ Evaluate and optimize the end-to-end latency of search and generation.

• Data Analysis

§ Collect, analyze, and interpret large datasets to identify trends, patterns, and insights that can inform business decisions.

• 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.

• Project Coordination and Stakeholder Collaboration

§ Collaborate with project managers, business analysts, and stakeholders to understand business requirements and translate them into technical solutions.

• Quality Assurance and testing

§ Collaborate with QA teams to validate data quality, ensure accuracy, and troubleshoot issues identified during testing.

• Continuous Improvement

• § Stay up-to on the latest tools, techniques, and best practices.
• § Identify opportunities for process improvements, optimizations, and automation.

• 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

Technical & Behavioral Competencies

Python, R, SQL

Machine learning algorithms

PyTorch or TensorFlow

Specific Qualifications

Data Scientist

Skills Referential (Required knowledge, skills and abilities)

Technical Skills

• Python
• Sql/Pl-Sql
• Machine learning algorithms
• RAG / Architecture
• CRM Schema

Behavioral Skills

• ​​Active listening​
• ​​Client focused​
• ​​Communication skills - oral & written​
• ​​Ability to deliver / Results driven​

Education Level: Any Graduation/Post Graduation

Location: Mumbai