Gen AI Engineer

We are looking for skilled Gen AI / Agentic AI Engineers and Leads to join our growing AI team. The ideal candidate will have hands-on experience in building, deploying, and scaling Generative AI and Agentic AI solutions using modern LLM frameworks, vector databases, cloud platforms, and MLOps practices. The role involves developing enterprise-grade AI applications, intelligent automation systems, and scalable AI architectures.

Key Responsibilities:

• Design, develop, and deploy Generative AI and Agentic AI applications for enterprise use cases.
• Build multimodal AI solutions involving text, image, and document processing.
• Develop and optimize GenAI pipelines, including data preprocessing, model training, evaluation, and deployment.
• Implement LLM orchestration using LangChain, LlamaIndex, Hugging Face Transformers, AutoGen, and OpenAI APIs.
• Develop Retrieval-Augmented Generation (RAG) systems with efficient chunking, embeddings, cross-encoders, and hybrid search techniques.
• Manage and optimize vector databases such as Pinecone, Weaviate, ChromaDB, FAISS, and Milvus.
• Implement MLOps and LLMOps practices, including CI/CD pipelines, model monitoring, automated testing, and drift detection.
• Work on prompt engineering and parameter-efficient fine-tuning techniques such as LoRA and QLoRA.
• Integrate AI models with enterprise systems using REST APIs, GraphQL, Kafka, and microservices architecture.
• Deploy AI workloads across AWS, Azure, or GCP using Docker, Kubernetes, and serverless technologies.
• Collaborate with cross-functional teams to develop scalable and production-ready AI solutions.

Required Skills & Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• 4–8 years of experience in Generative AI, Machine Learning, Software Engineering, or related domains.
• Strong hands-on experience in Generative AI and Agentic AI development.
• Proficiency in Python and modern AI/ML frameworks.
• Strong knowledge of LLMs, RAG architectures, Vector Databases, and Prompt Engineering.
• Experience with LangChain, LlamaIndex, Hugging Face, AutoGen, or similar frameworks.
• Experience deploying AI solutions on AWS, Azure, or GCP.
• Knowledge of scalable AI architecture, enterprise integrations, and microservices.
• Familiarity with MLOps, LLMOps, CI/CD, Docker, and Kubernetes.
• Strong problem-solving, analytical, and communication skills.
• Willingness to work from office 5 days a week.