# Senior backend and infra engineer

> Weekday AI · Bengaluru, India · Full-time · Posted 2026-09-26

**Salary:** INR 9,000,000–18,000,000

**Workplace:** on_site

**Department:** Weekday's Client via platform

## Description

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟵𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟭𝟴𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟵𝟬-𝟭𝟴𝟬 𝗟𝗣𝗔)

Experience: 5+ yrs

Location: Bengaluru, Karnataka, India

Job Type: Full-time

We are looking for an experienced **AI Research & Engineering Professional** to contribute to the development and improvement of next-generation AI systems in collaboration with leading frontier AI research organisations.

The role focuses on building the infrastructure, environments, evaluations, and high-quality enterprise data required to improve advanced AI models. You will work at the intersection of **AI research, software engineering, reinforcement learning, agentic systems, model evaluation, and data** to develop solutions that help measure and enhance the capabilities of increasingly sophisticated AI systems.

## Requirements

Key Responsibilities

-   Design and develop **reinforcement learning environments** for coding, reasoning, and agentic AI tasks.
-   Build infrastructure and tooling that enables advanced AI models to interact with realistic environments and complete complex tasks.
-   Develop robust **evaluation frameworks, benchmarks, and testing systems** to measure model capabilities and behaviour.
-   Design evaluation datasets, task suites, scoring mechanisms, and automated assessment pipelines.
-   Work with coding agents and agentic systems to evaluate planning, execution, reasoning, and task completion.
-   Develop scalable data pipelines and workflows for collecting, processing, validating, and managing enterprise AI data.
-   Improve data quality, consistency, coverage, and usability for model training and evaluation.
-   Analyse model outputs and evaluation results to identify capability gaps, failure patterns, and opportunities for improvement.
-   Build tools that enable reproducible experimentation and reliable comparison of model performance.
-   Collaborate with AI researchers and engineers to translate research requirements into production-quality systems.
-   Design and implement automated testing, monitoring, and quality-control mechanisms for AI workflows.
-   Investigate challenging technical problems involving model behaviour, evaluation reliability, data quality, and agent performance.
-   Contribute to experimentation involving **LLMs, reinforcement learning, AI agents, and model evaluation**.
-   Develop internal tools, frameworks, and reusable infrastructure to accelerate AI research and engineering workflows.
-   Document technical approaches, experimental results, evaluation methodologies, and system designs.
-   Continuously improve the reliability, scalability, and efficiency of AI research and production infrastructure.
-   Stay current with developments in **frontier AI, agentic systems, reinforcement learning, evaluation methodologies, and AI engineering**.

What Makes You a Great Fit

-   **5+ years of professional experience** in AI/ML engineering, software engineering, machine learning research, data engineering, or a closely related technical discipline.
-   Strong software engineering fundamentals with experience building **production-grade, scalable systems**.
-   Strong programming skills in **Python** and proficiency with modern software development practices.
-   Experience working with **LLMs, generative AI, AI agents, reinforcement learning, or model evaluation**.
-   Practical experience designing evaluation frameworks, benchmarks, datasets, or automated testing systems for AI/ML models.
-   Understanding of **reinforcement learning environments**, agentic workflows, or interactive AI systems is highly valuable.
-   Strong analytical and problem-solving skills with the ability to investigate complex model and system behaviour.
-   Experience working with structured and unstructured data and building reliable data-processing workflows.
-   Strong understanding of experimentation, reproducibility, metrics, benchmarking, and statistical evaluation.
-   Ability to translate ambiguous research problems into well-defined engineering solutions.
-   Experience building APIs, services, infrastructure, developer tooling, or distributed systems is an advantage.
-   Familiarity with cloud platforms, containers, CI/CD, databases, and modern engineering infrastructure.
-   Strong attention to **accuracy, reliability, data quality, and reproducibility**.
-   Ability to collaborate effectively with researchers, engineers, data specialists, and other technical stakeholders.
-   Comfortable working in a fast-moving environment where requirements evolve alongside emerging AI capabilities.
-   Strong curiosity about **frontier AI and the development of increasingly capable and reliable AI systems**.
-   Bachelor's or Master's degree in **Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a related technical discipline** is preferred.

## Apply

[Apply at Weekday AI](https://apply.workable.com/weekday-1/j/FCB33A301A/apply)

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