What are the responsibilities and job description for the Generative AI Engineer position at TalentOla?
ob Description:
We are seeking a Mid-Level Generative AI Developer with strong expertise in Python, AI-focused Python libraries, and AWS services to design, develop, and deploy cutting-edge AI solutions. The ideal candidate will have hands-on experience with AWS Bedrock, AWS Knowledge Base, and a deep understanding of LLM models. They also understand Retrieval-Augmented Generation (RAG) models, vector databases, and AWS Serverless Technologies to build scalable and efficient AI solutions.
Key Responsibilities:
- Develop and fine-tune Generative AI solutions using foundation models
- Develop and optimize AI solutions using Python and AI-related Python libraries
- Leverage AWS AI Services & AWS Serverless technologies to build & deploy intelligent AI-driven solutions.
- Ability to implement Retrieval-Augmented Generation (RAG) techniques using vector databases to improve AI responses.
- Work closely with cross-functional teams to design and deploy AI-driven applications in a cloud-native environment.
- Stay updated on emerging AI trends, best practices, and advancements in LLMs and generative AI models.
- Collaborate with data engineers and domain experts to integrate AI solutions into existing insurance platforms.
- Ensure compliance with industry regulations and data security standards while handling sensitive insurance data.
Required Skills & Qualifications:
- 3 years of experience in AI/ML development, with a focus on Generative AI and LLMs.
- Strong proficiency in Python and experience with AI/ML-focused libraries (e.g., PyTorch, TensorFlow, LangChain, Transformers).
- Hands-on experience with AWS Bedrock and AWS Knowledge Base.
- Solid understanding of LLM models (GPT, Claude, Llama, Falcon, etc.) and their applications.
- Experience with RAG (Retrieval-Augmented Generation) models and vector databases (e.g., Pinecone, OpenSearch).
- Expertise in AWS Serverless Technologies, including Lambda, API Gateway, Step Functions, S3, and DynamoDB.
- Familiarity with MLOps practices, CI/CD pipelines for AI models, and cloud-based AI deployment.
- Strong problem-solving skills, analytical thinking, and ability to work independently or in a team environment.
Preferred Qualifications:
- Knowledge of prompt engineering and techniques to enhance AI response accuracy.
- Exposure to multi-modal AI models (text, image, speech).
- Certification in AWS AI/ML services
- Experience with python AI/ML-focused libraries (e.g., Scikit-learn, pandas, Num-py).
- Knowledge of AWS AI services, such as Comprehend (NLP), Textract (document processing), Rekognition (image analysis), etc.