Gen AI Developer

AI Application Development

• Develop and deploy GenAI applications using leading LLM platforms and APIs.
• Create intelligent workflows and AI-powered business solutions leveraging modern orchestration frameworks.
• Translate business requirements into scalable AI features and reusable software components.
• Participate in the full development lifecycle from prototyping through production deployment.

Prompt Engineering & LLM Integration

• Design, test, and optimize prompts for consistent and high-quality LLM outputs.
• Develop reusable prompt templates and structured response frameworks.
• Implement techniques for output control, response validation, and prompt optimization.
• Support prompt testing and tuning to improve model performance and user experience.

RAG & Knowledge Retrieval Solutions

• Develop Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge applications.
• Integrate vector databases, embeddings, and semantic search capabilities.
• Build document ingestion, indexing, chunking, and retrieval workflows.
• Optimize retrieval quality, relevance, and response accuracy.

API & Microservices Development

• Design and build RESTful APIs and microservices to expose AI capabilities.
• Integrate GenAI solutions with enterprise applications, databases, and third-party platforms.
• Develop scalable backend services supporting AI-driven use cases.
• Ensure security, maintainability, and performance of deployed AI services.

Testing & Quality Assurance

• Develop testing strategies for prompts, workflows, and AI-generated outputs.
• Utilize synthetic datasets to validate AI use cases and edge cases.
• Monitor solution accuracy, reliability, and business performance metrics.
• Support evaluation and benchmarking activities for AI applications.

Collaboration & Innovation

• Work closely with AI Architects and Senior GenAI Engineers on enterprise AI initiatives.
• Participate in AI accelerators, reusable framework development, and innovation programs.
• Stay current with developments in LLMs, NLP, prompt engineering, and agentic AI technologies.
• Contribute to AI best practices, coding standards, and knowledge-sharing initiatives.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field. 
• 3–6 years of software development experience with at least 1–2 years focused on Generative AI solutions. 
• Strong foundation in Large Language Models (LLMs), NLP, prompt engineering, and AI application development. 
• Proficiency in Python and AI development frameworks. 
• Experience using LangChain or similar frameworks for workflow orchestration. 
• Experience developing prompt templates, structured outputs, and reusable AI components. 
• Hands-on experience building APIs and microservices for AI-driven applications. 
• Experience with embeddings, vector databases, and Retrieval-Augmented Generation (RAG) architectures. 
• Familiarity with synthetic data generation and AI testing methodologies. 
  • Strong problem-solving and debugging skills.