Principal Applied Science Engineer at Microsoft

Bangalore, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

28 Jan, 26

Salary

0.0

Posted On

30 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Natural Language Processing, Large Language Model Development, Evaluation, Fine-Tuning, Instruction Tuning, Reinforcement Learning from Human Feedback, Tool-Augmented Generation, Multi-Step Reasoning, Decision-Making, Prompt Engineering, Context-Aware Orchestration, Integration with External Tools, APIs, Experimentation, Agent Behavior Optimization, AI-Native Enterprise Applications

Industry

Software Development

Description

Do you want to shape the future of the autonomous enterprise and lead the development of intelligent, agent-first experiences that transform how businesses operate? The Business and Industry Solutions (BIS) team is looking for a Senior Applied Scientist to drive innovation at the intersection of AI, experimentation, and enterprise systems. In this role, you will design and evaluate autonomous agents that deliver measurable improvements in accuracy, latency, and cost-efficiency. You’ll lead rapid experimentation cycles, develop robust evaluation frameworks, and apply advanced techniques like reinforcement learning to enable multi-step reasoning and decision-making. You’ll collaborate across engineering, product, and partner teams to ensure agents are performant, secure, reliable, and extensible—empowering customers and partners to build on our platform. This is your opportunity to influence the next generation of AI-native business applications and deliver real-world impact at scale.   The ideal candidate has prior expertise in natural language processing (NLP), with a strong foundation in large language model (LLM) development, evaluation, and fine-tuning. They should have hands-on experience in applying advanced fine-tuning techniques—including instruction tuning, reinforcement learning from human feedback (RLHF), and tool-augmented generation—to build agents capable of multi-step reasoning and decision-making. Familiarity with prompt/context engineering, context-aware orchestration, and integrating LLMs with external tools and APIs is essential. The candidate should be comfortable working in a fast-paced, experimentation-driven environment, leveraging both offline and online evaluation methods to iterate rapidly and optimize agent behavior. A deep understanding of the challenges and opportunities in building AI-native enterprise applications will be key to success in this role. 

Responsibilities

The Principal Applied Science Engineer will design and evaluate autonomous agents to improve accuracy, latency, and cost-efficiency. They will lead rapid experimentation cycles and collaborate across teams to ensure agent performance and reliability.