S

Generative AI Developer

Sonata Software · Bengaluru, Karnataka, India

2–8 yrs experiencefull_timePosted 1w ago
Apply now →

Job description

**Job Summary:** We are seeking a passionate and skilled **Gen AI Developer** with hands-on experience in **AWS** and **Python** . The ideal candidate should have a strong foundation in building and deploying AI/ML models, with a focus on generative AI technologies. You will be responsible for designing, developing, and implementing solutions that leverage Gen AI capabilities on cloud platforms, primarily AWS. **Key Responsibilities:** - Design and develop applications using **Generative AI frameworks** (e.g., OpenAI, Hugging Face, LangChain, etc.) - Build and deploy AI/ML models on **AWS cloud infrastructure** - Develop backend components and services using **Python** - Integrate AI services into business applications using RESTful APIs - Collaborate with data scientists, cloud engineers, and product teams to translate business needs into technical solutions - Optimize model performance, monitor deployments, and troubleshoot issues in production - Ensure data security, compliance, and governance in AI solutions - Stay updated with advancements in Gen AI, AWS services, and ML/AI ecosystems **Required Skills:** - **36 years** of experience in software development with a strong focus on **Python** - Solid hands-on experience with **Generative AI** tools/frameworks such as OpenAI, Hugging Face, LangChain, etc. - Strong knowledge of **AWS services** like Sagemaker, Lambda, API Gateway, S3, EC2, etc. - Experience building and consuming **RESTful APIs** - Familiarity with **machine learning** concepts, model training, evaluation, and deployment - Version control with **Git/GitHub** - Experience with data handling using **Pandas, NumPy** , etc. - Knowledge of containerization tools like **Docker** is a plus **Preferred Qualifications:** - AWS Certification (Developer Associate / Machine Learning Specialty) is a plus - Experience working in an Agile/Scrum environment - Familiarity with DevOps practices and CI/CD pipelines