Join our team as a GEN AI Developer with 4-6 years of experience to build cutting-edge Generative AI applications. This role focuses on developing robust solutions using advanced frameworks and programming languages, with an immediate start.

We are seeking individuals who can architect and implement systems for handling large-scale data and integrate multi-modal LLM capabilities. This includes fine-tuning models for specific domains and ensuring seamless front-end integration for user interaction.

Your work will involve implementing LLMOps pipelines for efficient deployment and monitoring, alongside a strong commitment to Responsible AI practices and continuous innovation. This is a fantastic opportunity to contribute to groundbreaking AI projects.

- Develop GenAI applications from inception using frameworks such as Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. - Write efficient, high-quality Python code tailored for GenAI solutions. - Design and deploy architectures capable of managing extensive structured and unstructured data. - Implement multi-modal LLM applications, encompassing text, vision, and speech models. - Fine-tune Small Language Models (SLMs) for domain-specific requirements. - Integrate user interfaces using React, Streamlit, and AG Grid with GenAI backends. - Modernize and transform data pipelines to support advanced GenAI applications. - Apply fine-tuning techniques like PEFT, QLoRA, and LoRA for LLM optimization. - Establish and manage LLMOps pipelines for CI/CD and monitoring. - Embed ethical AI principles throughout the development lifecycle. - Drive innovation in Generative AI solutions.

- Demonstrate deep Python programming expertise for GenAI applications and automation. - Possess experience in productionizing GenAI applications beyond proof-of-concepts, utilizing frameworks like Pylint and Pyrit. - Exhibit proficiency in LLM frameworks such as Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. - Have a strong understanding of large-scale data handling architectures for structured and unstructured data. - Familiarity with multi-modal LLM applications, including text, vision, and speech models. - Experience fine-tuning SLMs for specialized data and use cases. - Knowledge of prompt injection fallback and RCE tools like Pyrit and HAX toolkit. - Familiarity with anti-hallucination and anti-gibberish tools such as Bleu. - Strong command of front-end technologies including React, Streamlit, AG Grid, and JavaScript. - Extensive experience with at least two cloud platforms (Azure, GCP, AWS) for GenAI application deployment. - Mastery of fine-tuning techniques like PEFT, QLoRA, and LoRA. - Solid understanding of LLMOps for model deployment, monitoring, and management. - Expertise in implementing Responsible AI practices and regulatory compliance. - Advanced skills in Retrieval-Augmented Generation (RAG) and Modular RAG. - Proficiency in data modernization and transformation for GenAI. - Experience with OCR and document intelligence tools. - Experience integrating APIs using REST, SOAP, and other protocols. - Expertise in building automated data curation and preprocessing pipelines. - Ability to produce clear technical documentation. - Excellent collaboration and communication skills for cross-functional teamwork.

Target companies include Quantiphi, Datastax, Coforge, HCL, Accenture, and Fractal.