Senior Software Engineer

Kamakhya Analytics Private Limited; Dadri; Sur place; INR 900 000 - 1 500 000; Plein temps

Résumé du poste

Kamakhya Analytics Private Limited seeks a senior backend/AI infra engineer to architect and manage database infrastructure and integrate AI/ML models into production.

You will lead AI-driven projects, design distributed cloud-native systems on AWS/GCP, and mentor junior engineers to ensure code quality and scalable solutions.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or related Engineering field.
• 4+ years of proven backend development and system architecture experience.
• Experience building database infrastructure and integrating AI/ML models into production.
• Proficiency with LLMs, prompts, and AI agent frameworks.

Responsabilités

• Database Infrastructure Management: architect, manage, and optimize complex DB infra across SQL, NoSQL, and vector databases.
• AI Agentic Development: lead AI-driven projects including intelligent agents and LLM-powered reporting & predictive modeling.
• System Architecture & Cloud: design distributed systems using AWS/GCP and containerization for high availability.
• Technical mentorship and ensuring code quality through reviews and best practices.

Connaissances

AI & ML integration

Database management

Cloud & DevOps

Architecture design

Formation

Bachelors or Masters in CS/IT/Engineering

Outils

LangChain

LlamaIndex

OpenAI APIs

PostgreSQL

MySQL

MongoDB

Pinecone

Milvus

Qdrant

Docker

Kubernetes

RabbitMQ

Kafka

Description du poste

Kamakhya Analytics is a technology-driven research and consulting organisation helping leaders, parties, and institutions decode India’s political and policy landscape. We bring together survey science, data analytics, and strategic insight to answer complex questions about public opinion, governance, and performance. From ground-level fieldwork to advanced modelling and interpretation, every project is built for clarity, accuracy, and impact. Our teams manage the complete research cycle, design, execution, data engineering, and delivery under a single framework of discipline, transparency, and speed. Quality and integrity define our work. We apply rigorous controls in sampling and verification, maintain secure and reproducible data systems, and communicate results that withstand scrutiny.

At Kamakhya, our mission is simple: turn evidence into strategy and insight into action.

About the Team

Role Overview

• Database Infrastructure Management: Architect, manage, and optimize complex database infrastructures. Handle the ingestion, storage, and retrieval of high-velocity structured and unstructured data across SQL, NoSQL, and Vector databases.
• AI Agentic Development: Lead the technical implementation of AI-driven projects, including the development of intelligent agents and LLM-powered systems for automated reporting, sentiment analysis, and predictive modeling.
• System Architecture & Cloud: Design distributed systems and deploy applications utilizing modern cloud infrastructure (AWS/GCP) and containerization to guarantee high availability and fault tolerance.
• Technical Mentorship & Code Quality: Set the standard for engineering excellence by writing clean, maintainable code. Conduct rigorous peer code reviews and mentor junior developers on best practices in backend and AI engineering.

Required Skills & Qualifications:

Education

• A Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related Engineering field.
• Relevant certifications in Cloud Architecture (AWS/GCP) or AI/Machine Learning are highly advantageous.

Experience

• A minimum of 4 years of proven experience in software engineering, with a strong focus on backend development and system architecture.
• Hands-on experience building database infrastructure from the ground up and integrating AI/ML models into production environments.

Skills

• AI & Machine Learning Integration: Practical experience with Large Language Models (LLMs), prompt engineering, and AI agent frameworks (e.g., LangChain, LlamaIndex, or OpenAI APIs). Database Management: Expert-level proficiency in relational databases (PostgreSQL/MySQL), NoSQL databases (MongoDB), and familiarity with Vector databases (Pinecone, Milvus, or Qdrant) for AI applications.
• Cloud & DevOps: Extensive experience with cloud service providers (AWS/GCP), container orchestration (Docker/Kubernetes), and CI/CD pipelines.
• Architecture: Strong understanding of microservices architecture, asynchronous programming, and message brokers (e.g., RabbitMQ, Kafka).