Sr. Test Engineer/ Associate Staff Test Engineer(Backend)

Tally Solutions; Bengaluru; Hybrid; INR 2,400,000 - 4,200,000; Full time

Job summary

Tally Solutions in Bengaluru is seeking a Backend Lead to guide our AI-focused backend team. The role emphasizes performance, scalability, and mentoring engineers, with deep Python expertise and experience in building scalable systems.

We value leadership in backend development, drive for complex technical initiatives, and strong knowledge of modern testing, CI/CD, and cloud-native architectures. Join an engineering centre in Bangalore focused on cutting-edge backend solutions.

Qualifications

• Strong understanding of testing across the software lifecycle (STLC) and Agile practices.
• Ability to analyse requirements and design effective test strategies and coverage.
• Hands-on automation with Playwright/Selenium/Cypress and proficiency in Python, Java, JavaScript/TypeScript.
• Strong API and performance testing using Postman, REST Assured, JMeter, Gatling or k6.
• Good understanding of microservices, distributed systems, databases and cloud-native architectures.

Responsibilities

• End-to-End Deployment Testing: collaborate with backend engineers to deploy models via Docker/Kubernetes and design end-to-end test strategies (on-prem and cloud).
• CI/CD Automation: maintain robust CI/CD pipelines and drive test automation for faster releases.
• Research Distillation: explore open-source models and apply knowledge distillation for compact, fast proprietary models.
• Monitor Improve: continuously monitor drift, hallucination rates, and retrieval quality in production systems.
• Code Quality & Best Practices: ensure clean code, testing, and documentation.

Skills

Python

Backend Lead

STLC & Agile

API Testing

Cloud & Docker

Observability

Tools

Docker

Kubernetes

Git

Grafana

ELK

Job description

Job Summary

We are seeking a highly skilled and experienced Backend Lead to join our AI team. As a Backend Lead, you will play a crucial role in ensuring the performance, scalability, and efficiency of our backend architecture while mentoring and leading a team of engineers. This position requires deep expertise in backend engineering, particularly in Python, and a strong understanding of building scalable and efficient systems. The ideal candidate will have a proven track record of leadership in backend development, and the ability to drive complex technical initiatives. Our Engineering centre is located in Bangalore while our sales offices and partners are spread across the country and specific regions outside India.

Where Your Expertise Meets Our Future

• Strong understanding of STLC, Agile and modern Quality Engineering practices, with expertise in functional, integration, API, regression, end to end, non-functional testing and compatibility testing.
• Ability to analyse requirements and system workflows, design effective test strategies, test scenarios, and risk-based test cases, and ensure comprehensive functional and non-functional coverage.
• Hands-on automation experience with Playwright/Selenium/Cypress and proficiency in Python, Java, JavaScript or TypeScript.
• Strong API and performance testing experience using tools such as Postman, REST Assured, JMeter, Gatling or k6.
• Good understanding of microservices, distributed systems, networking, databases and cloud-native architectures.
• Hands-on exposure to AWS/Azure/GCP, Docker/Kubernetes, CI/CD pipelines and Git-based workflows.
• Experience with observability, debugging and RCA using logs, metrics and monitoring tools such as Grafana, CloudWatch or ELK.
• Exposure to AI-assisted testing/development and testing of AI/LLM-based applications is an added advantage.

The Scope of Your Influence

• End-to-End Deployment Testing: Collaborate with backend engineers to deploy models via Docker/Kubernetes, and design end-to-end test strategies (on-prem and cloud) grounded in system architecture.
• CI/CD Automation: Maintain robust CI/CD pipelines and drive continuous test automation to minimize turnaround time for new releases.
• Research Distillation: Actively research state-of-the-art open-source models (e.g., Qwen3, Mistral) and apply Knowledge Distillation to create smaller, faster proprietary models.
• Monitor Improve: Continuously monitor drift, hallucination rates, and retrieval quality in production systems.
• Code Quality and Best Practices: Ensure that code adheres to best practices, including clean code principles, testing, and documentation.
• Build Agentic Systems: Implement multi-agent workflows using LangGraph to solve complex, multi-step user queries.
• Optimize for Scale: Implement Quantization and vLLM/SGLang strategies to reduce inference costs and latency in production.