Role Overview:

As a Senior Prompt Engineer based in Hyderabad, you will sit at the intersection of cutting-edge research and practical business application, architecting the interactions between human intent and machine intelligence. You will work closely with cross-functional teams of data scientists, product managers, and software engineers to design, test, and refine sophisticated prompt strategies that drive high-performance Generative AI solutions.

Key Responsibilities:

- Engineer and iterate on complex prompt chains and system instructions to maximize the accuracy and reasoning capabilities of LLMs across diverse enterprise use cases.

- Architect and deploy scalable RAG frameworks to ensure AI models provide grounded, fact-based insights derived from proprietary organizational data.

- Collaborate with engineering teams to integrate LangChain and LangGraph workflows, enabling the development of autonomous agents capable of multi-step task execution.

- Evaluate and benchmark model performance on Azure Foundry, identifying opportunities to reduce latency and improve output quality for production-grade applications.

- Translate ambiguous business requirements into structured technical prompts and evaluation metrics to ensure consistent alignment with stakeholder expectations.

- Mentor junior team members on best practices in NLP and prompt optimization to foster a culture of technical excellence and continuous innovation.

Required Skillset:

- Demonstrated expertise in designing and optimizing prompts for large-scale LLMs, with a deep understanding of tokenization, context window management, and model behavior.

- Proven ability to build and maintain production-ready RAG architectures, ensuring seamless integration between vector databases and generative models.

- Proficiency in leveraging LangChain and LangGraph to orchestrate complex AI workflows, coupled with a strong grasp of Python and modern machine learning libraries.

- Hands-on experience working within the Azure Foundry ecosystem to deploy, monitor, and fine-tune AI models for enterprise environments.

- Exceptional communication skills with the ability to articulate complex technical concepts to non-technical stakeholders and cross-functional partners.

- A strong analytical mindset, typically supported by an advanced degree in Computer Science, Data Science, or a related quantitative field, with 5 - 8 years of relevant industry experience.

- High degree of adaptability and comfort working in a hybrid environment, demonstrating the ability to collaborate effectively with distributed teams in a fast-paced setting.