Research Scientist, Applied AI

Weekday; Bengaluru; Hybrid; INR 9,000,000 - 10,000,000; Full time

Benefits offered by this job

Remote role in India

Equity at Series A

Direct work with Head of AI

Job summary

Weekday is seeking a senior AI research engineer to build the core agent behavior behind a revenue-focused AI agent, from the harness and evals to fine-tuning and reinforcement learning, and to take hard research problems from hypothesis to production.

You will own the agent harness, tool orchestration, context management, evaluation pipelines, RL approaches, and collaborate with the Head of AI in the US and the applied AI team in India.

Qualifications

• 5+ years of applied AI research or applied science at senior level.
• MS or PhD in Computer Science, Mathematics, Statistics, or a quantitative discipline.
• Hands-on experience building agentic systems and agent harnesses, including tool use and multi-step reasoning.
• Experience with LLMs or large-scale deep learning systems, including RLHF and fine-tuning.
• Understanding of model behavior beyond usage, and ability to design eval datasets/frameworks.
• Publications at top-tier conferences or journals preferred.

Responsibilities

• Own and advance the agent harness, core loop, tools, environment, guardrails, and model behavior.
• Improve tool selection, context building, cross-sub-agent coordination, and long multi-step tasks.
• Drive model selection balancing quality, latency, and cost.
• Design and build evaluations for revenue tasks with benchmarks and automated eval pipelines.
• Build eval datasets and grading methods for tasks without ground truth.
• Lead fine-tuning as the platform moves toward deeper model training.
• Research RL approaches to improve agent behavior.
• Enhance context engineering and data quality via entity resolution and knowledge graphs.
• Own ambiguous research problems end-to-end and ship results to production.
• Collaborate with US Head of AI and India applied AI team.

Skills

Agentic systems

LLMs

RLHF

Context management

Research publications

US time zone coordination

Education

MS/PhD in CS/Math/Stats

Tools

LLM platforms

Deep learning frameworks

Training and fine-tuning

Job description

This role is for one of Weekday’s clients
Salary range: Rs 9000000 - Rs 10000000 (ie INR 90 - 100 LPA)

Min Experience: 5+ years
Location: Remote (India)
JobType: full-time

About the Role

Build the core agent behaviour behind a revenue-focused AI agent, from the agent harness and evals to fine-tuning and reinforcement learning, and take hard research problems from hypothesis to production.

Key Responsibilities

• Own and advance the agent harness: the core loop, tools, environment, guardrails, and model behaviour that power the agent.
• Improve how the agent selects tools, builds context, coordinates across sub-agents, and handles long, multi-step tasks, through systematic experimentation.
• Drive model selection across tasks, balancing answer quality, latency, and cost.
• Design and build evaluations for complex revenue tasks such as deal health, risk, and pipeline questions, including benchmarks, regression detection, and automated eval pipelines.
• Build eval datasets and grading methods for tasks that have no clean ground truth.
• Build scoring and prediction models, such as deal health scores from call transcripts and emails, cross-deal pattern mining, and explainable risk signals.
• Lead fine-tuning work as the platform moves from harness-heavy work into deeper model training.
• Research and design reinforcement learning (RL) approaches that improve agent behaviour.
• Improve context engineering and data quality through entity resolution, information extraction, and knowledge and context graphs.
• Own ambiguous research problems end-to-end: form hypotheses, design experiments, build the training, eval, and grading infrastructure, and ship results to production.
• Work closely with the US-based Head of AI and the applied AI team in India.

Qualifications

• 5+ years of experience in applied AI research or applied science, at a senior level.
• MS or PhD in Computer Science, Mathematics, Statistics, or another quantitative discipline.
• Hands-on experience building and improving agentic systems and agent harnesses, including tool use, multi-step reasoning, and context management.
• Hands-on experience with LLMs or large-scale deep learning systems, including training, fine-tuning, and RLHF.
• A clear understanding of why models behave the way they do, not only how to use them.
• Experience designing eval datasets or frameworks, especially for tasks without clean ground truth.
• Proven ability to scope and drive ambiguous research with minimal guidance.
• Publications at top-tier peer-reviewed conferences or journals are preferred.
• Comfortable working with a US-based leadership team across time zones.

Benefits & Perks

• Competitive salary and equity at Series A, ahead of the next funding round.
• A remote role, with the team meeting in person in Bangalore.
• Meaningful scope from day one: you will own core agent capabilities, not just support them.
• Direct work with the Head of AI and a tight feedback loop with founders and product.
• A sharp, low-ego team that moves fast and communicates directly.
• A chance to shape an AI-first product at a pivotal stage, as it moves from harness work into fine-tuning and RL.

Must-have skills

Agentic Systems, Agent Harness Design, model finetuning

Good-to-have skills

LLM, Applied AI, AI research