Research Scientist, Applied AI

. Own and advance the agent harness: the core loop, tools, environment, guardrails, and model behaviour that power the agent .

Posted 10/22/2026full-timeRemote • IndiaMid-LevelSenior💰 ₹9,000,000 - ₹10,000,000 per yearWebsite

Key responsibilities & impact

Own and advance the agent harness: the core loop, tools, environment, guardrails, and model behaviour that power the agent
Improve agent tool selection, context construction, sub-agent coordination, and handling of long, multi-step tasks through systematic experimentation
Drive model selection across tasks while balancing answer quality, latency, and cost
Design and build evaluations for complex revenue tasks, including benchmarks, regression detection, and automated evaluation pipelines
Build evaluation datasets and grading methods for tasks without clean ground truth
Build scoring and prediction models, including deal health scores, cross-deal pattern mining, and explainable risk signals
Lead fine-tuning work as the platform moves into deeper model training
Research and design reinforcement learning 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 training, evaluation, and grading infrastructure, and ship results to production
Work closely with the US-based Head of AI and applied AI team in India

What you’ll need

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
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
Comfortable working with a US-based leadership team across time zones
Publications at top-tier peer-reviewed conferences or journals are preferred

Comp & perks

Competitive salary and equity at Series A, ahead of the next funding round
Remote role
Team meeting in person in Bangalore
Meaningful scope from day one: ownership of core agent capabilities
Direct work with the Head of AI and a tight feedback loop with founders and product
Opportunity to shape an AI-first product at a pivotal stage