Generative AI Developer / Engineer/Analyst

Overview

Build end-to-end, production-grade Generative AI applications using internal or private LLM platforms, with a focus on security, reliability and enterprise integration.

What you'll do

• Design, develop and optimize applications leveraging internal LLM platforms.
• Create, test and maintain high-quality prompts to drive accurate and predictable outputs.
• Apply advanced prompting techniques including few-shot prompting, prompt chaining and RAG (Retrieval-Augmented Generation).
• Establish prompt evaluation and versioning practices.
• Build full-stack, end-to-end GenAI applications.
• Design and implement backend services integrating LLMs with enterprise systems.
• Develop or collaborate on web-based user interfaces.
• Integrate GenAI capabilities into existing applications and workflows.
• Work with modern web technologies such as REST APIs and web frameworks (React, Angular, Vue, or equivalent).
• Build backend services using Node.js, Java, Python, .NET, etc.
• Build scalable, maintainable application architectures.
• Analyze structured and unstructured data for GenAI use cases.
• Translate business requirements into LLM-driven workflows.
• Perform data validation, transformation and analysis to support AI pipelines.
• Collaborate with automation teams.
• Build solutions aligned with enterprise security, compliance and governance standards.
• Work with private or internal LLMs, ensuring data privacy and controlled usage.
• Document design decisions, prompts and system behavior clearly.

What you'll need

• 2 to 3 years of experience building GenAI or LLM-based applications.
• 1 to 3 years of hands-on experience with prompt engineering.
• 2 to 3 years of data analysis or business analysis experience.
• Strong written English skills.
• Ability to code in at least one modern programming language.
• Experience building end-to-end applications, not just models or scripts.
• Experience with internal or private LLM platforms.
• Experience with RAG architectures and vector search.
• Experience with APIs and service-oriented architecture.
• Solid understanding of LLM limitations (hallucinations, bias, drift).
• Experience with evaluation and validation of model outputs.
• Understanding of cost, latency and performance trade-offs.
• Strong analytical and problem-solving skills.
• Ability to explain GenAI behavior to technical and non-technical audiences.

Nice to have

• Blue Prism RPA experience.
• Experience with enterprise web applications.
• Familiarity with LLMOps or MLOps concepts.
• Knowledge of document-heavy domains such as contracts, agreements and reports.
• Experience working in regulated or enterprise environments.

Details

• Location: Remote, Karnataka.