Senior Software Engineer

Responsibilities

1. RAG Architecture & Pipeline Design

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

1. Vector Search & NLP

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

1. MCP Server Development

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

1. Generative AI Integration

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

1. Performance Optimization

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

1. Data Analysis

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

1. 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.

1. Project Coordination and Stakeholder Collaboration

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

1. Quality Assurance and testing

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

1. Continuous Improvement

§ Stay up-to on the latest tools, techniques, and best practices.

§ Identify opportunities for process improvements, optimizations, and automation.

1. 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