Senior backend and infra engineer

Weekday 1; Bengaluru; On-site; INR 5,000,000 - 18,000,000; Full time

Job summary

Weekday 1 is seeking an experienced AI Research & Engineering Professional to develop next-gen AI systems in collaboration with frontier AI researchers.

The role spans AI research, software engineering, reinforcement learning, agentic systems, model evaluation, and data infrastructure to build scalable, production-ready solutions for enterprise AI. Location is Bengaluru, India, with a full-time employment arrangement.

Qualifications

• 5+ years of professional experience in AI/ML engineering, software engineering, machine learning research, data engineering.
• Strong software engineering fundamentals with production-grade, scalable systems.
• Proficient in Python and modern software development practices.
• Experience with LLMs, generative AI, AI agents, reinforcement learning, or model evaluation.
• Experience designing evaluation frameworks, benchmarks, datasets, or automated testing systems.
• Understanding reinforcement learning environments and agentic workflows is highly valuable.
• Strong analytical and problem-solving skills with the ability to investigate complex model and system behaviour.
• Experience with structured and unstructured data processing workflows.
• Knowledge 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 emphasis on accuracy, reliability, data quality, and reproducibility.
• Ability to collaborate with researchers and engineers.

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.

Skills

AI/ML engineering

Python programming

Reinforcement learning

LLMs

Model evaluation

Data engineering

Education

Bachelor's or Master's degree in CS/AI/ML/Engineering

Tools

Cloud platforms

Containers

CI/CD

Databases

Job description

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

Salary range: 𝗥𝘀 5,000,000 - 𝗥𝘀 18,000,000 (i.e. INR 90-180 LPA)

Experience: 5+ yrs

Location: Bengaluru, Karnataka, India

Job Type: Full-time

We are looking for an experiencedAI Research & Engineering Professionalto 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 ofAI research, software engineering, reinforcement learning, agentic systems, model evaluation, and datato develop solutions that help measure and enhance the capabilities of increasingly sophisticated AI systems.

Requirements

Key Responsibilities

• Design and developreinforcement learning environmentsfor 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 robustevaluation frameworks, benchmarks, and testing systemsto 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 involvingLLMs, 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 infrontier AI, agentic systems, reinforcement learning, evaluation methodologies, and AI engineering.

What Makes You a Great Fit

• 5+ years of professional experiencein AI/ML engineering, software engineering, machine learning research, data engineering, or a closely related technical discipline.


• Strong software engineering fundamentals with experience buildingproduction-grade, scalable systems.


• Strong programming skills inPythonand proficiency with modern software development practices.


• Experience working withLLMs, 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 ofreinforcement 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 toaccuracy, 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 aboutfrontier AI and the development of increasingly capable and reliable AI systems.


• Bachelor's or Master's degree inComputer Science, Artificial Intelligence, Machine Learning, Engineering, or a related technical disciplineis preferred.