Software Engineer - Prompt Engineer

Hiring Software Engineers with strong skills in Python, NLP / ML, and cloud-native development who can design, develop, and optimize prompt-driven AI systems.

Salary : INR 20,00,000 - 30,00,000 / year

Responsibilities

• Design, test, and optimize prompts for LLM-based applications (chatbots, automation agents, RAG systems).
• Build reusable prompt templates and orchestration logic for various tasks.
• Evaluate LLM responses and improve output quality through experimentation, pattern design, and prompt refinement.
• Implement NLP and text-processing pipelines as needed.
• Integrate open-source or hosted LLM APIs into backend services.
• Build small ML components (classification, embeddings, vector search) supporting AI workflows.
• Work with retrieval systems, embeddings, and context optimization.
• Develop and maintain Python-based microservices built around AI components.
• Build scalable backend services using modern REST APIs and asynchronous frameworks.
• Implement clean, modular, production-grade code following engineering best practices.
• Deploy microservices and AI pipelines on Azure Cloud (App Service, AKS, Functions, etc.).
• Build automated CI / CD pipelines using Azure DevOps or similar tools.
• Manage containerized workloads using Docker and Kubernetes.
• Monitor performance and ensure high availability of AI-driven services.

Eligibility

Roles and openings are subject to change. The client reserves the right to modify, reassign, or withdraw any role, requirements, number of positions, or timelines at any time during the hiring process. Submission of an application does not guarantee assignment to a particular role or an offer of employment. Applicants may be asked to attempt a hackathon assessment as a part of the hiring process. All hires are contingent on standard pre-employment screening and eligibility verification.

Skills : microservices,python,nlp,ci / cd,azure cloud,kubernetes,machine learning

Skills Required

Machine Learning, Nlp, Azure Cloud, Python, Kubernetes, Microservices