# Chief Information Security Officer (CISO)

> Weekday AI · Delhi, India · Full-time · Posted 2026-09-19

**Salary:** INR 5,000,000–20,000,000

**Workplace:** on_site

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

## Description

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟱𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟮𝟬𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟱𝟬-𝟮𝟬𝟬 𝗟𝗣𝗔)

Experience: 8+ yrs

Location: India

Job Type: Full-time

We are looking for an experienced and technically strong **AI Research & Engineering Leader** to work on advanced artificial intelligence initiatives focused on improving the capabilities, reliability, and evaluation of frontier AI models.

The role sits at the intersection of **AI research, machine learning engineering, model evaluation, reinforcement learning, agentic systems, coding environments, and enterprise data**. You will contribute to building sophisticated environments, evaluation systems, and high-quality data solutions that help advance the capabilities of next-generation AI models.

The ideal candidate combines strong technical depth with the ability to work on ambiguous, research-oriented problems and translate emerging AI concepts into robust, scalable systems.

## Requirements

Key Responsibilities

-   Lead the design and development of advanced **AI research and engineering systems** for frontier AI models.
-   Build sophisticated **reinforcement learning environments** for coding, reasoning, tool use, and agentic workflows.
-   Design environments that allow AI agents to interact with realistic software systems, tools, APIs, and external resources.
-   Develop robust **model evaluation frameworks, benchmarks, and test environments** to measure AI capabilities and reliability.
-   Create automated evaluation pipelines for LLMs, AI agents, coding systems, and reasoning workflows.
-   Investigate model behaviour, identify capability gaps, and design experiments to improve performance.
-   Develop and manage high-quality datasets, including **enterprise and synthetic data**, for AI training and evaluation.
-   Build scalable infrastructure for experimentation, evaluation, data processing, and AI workflows.
-   Develop systems for automated testing, benchmarking, regression detection, and continuous model evaluation.
-   Work on **agentic AI architectures**, including planning, tool calling, multi-step reasoning, memory, and environment interaction.
-   Design and execute controlled experiments to test new AI methodologies and approaches.
-   Analyse experimental results and translate findings into actionable technical and research decisions.
-   Collaborate closely with AI researchers, ML engineers, software engineers, and data specialists.
-   Establish scalable, reproducible, and observable engineering practices for AI experimentation.
-   Evaluate emerging AI technologies and research techniques and identify opportunities for practical application.
-   Drive technical architecture, system design, implementation, and productionisation of successful research initiatives.
-   Mentor engineers and researchers while establishing strong technical and engineering practices.
-   Document methodologies, experiments, evaluation results, system architectures, and technical learnings.

What Makes You a Great Fit

-   **8+ years of experience** in AI/ML engineering, research engineering, machine learning, software engineering, or a closely related technical field.
-   Deep understanding of **Generative AI, Large Language Models, reinforcement learning, and modern AI systems**.
-   Proven experience building sophisticated AI/ML systems, research infrastructure, or production-grade machine learning platforms.
-   Strong programming expertise in **Python** and modern AI/ML frameworks.
-   Strong experience with **LLM evaluation, benchmarking, experimentation, and model behaviour analysis**.
-   Experience designing evaluation frameworks, task environments, automated benchmarks, or model assessment systems.
-   Practical experience with **agentic AI, AI agents, coding agents, tool use, or multi-step reasoning systems**.
-   Strong understanding of reinforcement learning concepts, environments, rewards, training loops, or RL-based optimisation.
-   Experience working with large-scale, synthetic, enterprise, or specialised datasets for AI applications.
-   Strong software engineering fundamentals across system design, APIs, distributed systems, testing, observability, and production reliability.
-   Experience working with cloud infrastructure, distributed computing, GPUs, or large-scale ML platforms is an advantage.
-   Strong research mindset with the ability to formulate hypotheses, design experiments, analyse results, and iterate rapidly.
-   Excellent problem-solving and debugging skills with the ability to tackle highly ambiguous technical challenges.
-   Strong communication and collaboration skills when working with research and engineering teams.
-   Demonstrated ability to take ownership of complex initiatives from concept and experimentation through implementation and evaluation.
-   Advanced degree in **Computer Science, Artificial Intelligence, Machine Learning, Mathematics, or a related technical field** is advantageous, though exceptional equivalent industry experience may also be considered.

## Apply

[Apply at Weekday AI](https://apply.workable.com/weekday-1/j/0E9EF58F8E/apply)

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