GEN AI Sr. Developer

PFB the JD:

Senior Developer- Gen AI Application Development

Senior Developer-GenAI Application shall be focused on coding, developing, and implementing GenAI applications using fine-tuned LLMs (Large Language Models) and SLMs (Small Language Models). This role emphasizes hands-on expertise in open-source frameworks, libraries, and cloud tools, with the ability to quickly prototype and demonstrate GenAI applications. The developer shall work under the guidance of senior team members to deliver high-quality, scalable, and innovative solutions.

Key Responsibilities:

• Coding and Development : Write clean, using Lang chain/Lang graph and Auto Gen frameworks efficiently, and maintainable code for GenAI applications using Python and open-source frameworks.


• Fine-Tuning Models : Fine-tune LLMs and SLMs using techniques like PEFT, LoRA, and QLoRA for specific use cases.


• Open-Source Frameworks : Work with frameworks like Hugging Face, LangChain, and others to build GenAI solutions.


• Azure AI Expertise : Design and deploy scalable AI solutions leveraging a comprehensive suite of Azure AI services.


• Integration and Deployment: Integrate generative AI models into existing enterprise systems and applications. Implement robust MLOps practices, CI/CD pipelines (e.g., Azure DevOps, GitHub, Jenkins), and containerization (Docker, Kubernetes) for seamless deployment. Knowledge of AWS would be an added advantage.


• Data Preprocessing : Build and maintain data preprocessing pipelines for training and fine-tuning models.


• API Integration : Integrate REST, SOAP, and other APIs for data ingestion, processing, and output delivery.


• Model Evaluation : Evaluate model performance using metrics and benchmarks and iterate to improve results.


• Prototyping : Quickly prototype and demonstrate GenAI applications to showcase capabilities and gather feedback.


• Front-End Development : Collaborate with front-end developers to integrate GenAI capabilities into user-friendly interfaces using tools like Streamlit or React.


• Version Control : Use Git and other version control systems to manage code and collaborate with team members.

• Technical Documentation : Create clear and concise documentation for code, models, and processes.


• Collaboration : Work closely with data scientists, engineers, and product managers to deliver high-impact solutions.


• Learning and Growth : Continuously learn and stay updated with the latest advancements in GenAI, open-source tools, and cloud technologies.


• Debugging and Optimization : Identify and fix bugs, optimize code, and improve application performance.

Required Skills:

• Python Programming : Strong proficiency in CORE Python OOP for developing GenAI applications.


• Fine-Tuning Techniques : Hands-on experience with fine-tuning methods like PEFT, LoRA, and QLoRA.


• Open-Source Frameworks : Expertise in Hugging Face, LangChain, LlamaIndex, and other open-source libraries.


• Cloud Platforms : Familiarity with Azure, GCP, and AWS for deploying and managing GenAI models.


• Data Preprocessing : Skills in building and maintaining data preprocessing pipelines.


• API Integration : Experience with REST, SOAP, and other protocols for API integration.


• Model Evaluation : Knowledge of metrics and benchmarks for evaluating model performance.


• Front-End Tools : Basic knowledge of front-end tools like Streamlit, React, or JavaScript for UI integration.


• Version Control : Proficiency in Git and Version Control best practices.


• Technical Documentation : Ability to create clear and concise technical documentation.


• Problem-Solving : Strong analytical and problem-solving skills to debug and optimize code.


• Collaboration : Excellent teamwork and communication skills to work effectively in cross-functional teams.


• Rapid Prototyping : Ability to quickly prototype and demonstrate GenAI applications.


• Continuous Learning : A growth mindset with a passion for learning and staying updated with the latest GenAI trends and technologies.

Good to have:

• Document Intelligence : Proficiency in OCR and document intelligence using open-source and cloud tools.