SMARTnCODE - Generative AI Engineer/LLM Integration Specialist

Position : AI/GenAI Engineer (LLM Integration Specialist)

Experience : 2 - 4 years

CTC : 12 to 16 LPA

Location : Hyderabad

About the Role :

We're building a high-performance chat application and looking for an AI/GenAI Engineer to lead the integration and optimization of Large Language Models (LLMs). You'll be responsible for connecting LLM APIs, implementing domain-specific fine-tuning strategies, prompt engineering, and ensuring optimal performance for production use.

Key Responsibilities :

LLM Integration & Architecture :

• Integrate multiple LLM APIs (OpenAI, Anthropic Claude, Google Gemini, or open-source models)
• Design and implement robust API wrapper services with retry logic, fallback mechanisms, and error handling
• Implement streaming responses for real-time chat experience
• Build rate limiting and quota management systems
• Handle token counting, context window management, and cost optimization

Domain Customization & Fine-tuning :

• Develop domain-specific prompt engineering strategies
• Implement RAG (Retrieval Augmented Generation) pipelines using vector databases
• Fine-tune or adapt models for specific use cases using techniques like LoRA, prompt tuning
• Create and maintain knowledge bases for domain-specific responses

Performance & Optimization :

• Optimize API response times and reduce latency
• Implement caching strategies for common queries
• Monitor and optimize token usage to control costs

Safety & Quality :

• Implement content moderation and safety filters
• Build guardrails to prevent prompt injection and jailbreaking
• Develop evaluation frameworks to measure response quality

Technical Stack :

• Languages : Python (primary), JavaScript/TypeScript (basic understanding)
• LLM APIs : OpenAI, Anthropic, Google Gemini, Cohere
• Frameworks : LangChain, LlamaIndex, FastAPI
• Vector DBs : Pinecone, Weaviate, Qdrant, or ChromaDB
• Infrastructure : Docker, Redis, PostgreSQL, Message Queues
• Cloud : AWS/GCP/Azure

Infrastructure :

• Design scalable architecture for handling concurrent LLM requests
• Implement queue systems for managing high-volume API calls
• Set up monitoring and logging for LLM interactions
• Work with DevOps to deploy models (if self-hosted)

Required Skills & Experience :

Must Have

• Experience working with LLMs and GenAI technologies
• Strong experience with OpenAI API, Anthropic Claude, or similar LLM APIs
• Proficiency in Python (FastAPI, LangChain, LlamaIndex preferred)
• Strong understanding of prompt engineering techniques and best practices
• Experience with vector databases (Pinecone, Weaviate, Qdrant, ChromaDB)
• Knowledge of RAG (Retrieval Augmented Generation) implementation
• Understanding of transformer architecture and attention mechanisms
• Experience with API integration, webhooks, and streaming responses
• Strong problem-solving skills and ability to debug complex AI systems
• Experience with LangChain, LlamaIndex, or similar LLM frameworks
• Knowledge of fine-tuning techniques (LoRA, QLoRA, PEFT)
• Experience with embedding models and semantic search
• Familiarity with HuggingFace Transformers library
• Experience deploying models using vLLM, TGI (Text Generation Inference)
• Knowledge of function calling/tool use with LLMs
• Experience with model evaluation metrics (BLEU, ROUGE, BERTScore)
• Understanding of token economics and cost optimisation
• Experience with open-source models (Llama, Mistral, Falcon)
• Knowledge of model quantization and optimization techniques
• Experience with multi-modal models (vision, audio)
• Familiarity with MLOps practices and experiment tracking (Weights & Biases, MLflow)
• Experience with AWS SageMaker, Google Vertex AI, or Azure ML
• Understanding of chain-of-thought prompting, ReAct, agents
• Experience building chatbots or conversational AI systems
• Publications or contributions to AI/ML community