Generative ai engineer

4 weeks ago

Hyderabad, India Winfo Solutions Full time

About the Role We are looking for a Generative AI Engineer with strong software engineering skills and hands-on experience in developing AI-powered applications . This role involves coding AI-driven solutions, developing APIs, integrating models into products, and building scalable AI systems for production use. Key Responsibilities: · Develop AI-driven applications by integrating LLMs and generative models into real-world software solutions. · Design and build APIs for LLMs and Gen AI models (Fast API, Flask, Django). · Write production-ready code to integrate AI features into web applications, chatbots, document processing tools, and recommendation systems. · Fine-tune and optimize LLMs (GPT, LLa MA, Gemini, Claude, Mistral) for performance in real-time applications. · Develop AI-powered chatbots, document extraction tools, and automation systems using Lang Chain, Haystack, or Semantic Kernel. · Implement vector search using FAISS, Chroma DB, or Pinecone for retrieval-augmented generation (RAG) applications. · Work with databases (Postgre SQL, Mongo DB, Redis) to manage AI-driven data workflows. · Build scalable AI microservices and integrate them into enterprise applications . · Collaborate with backend engineers, data engineers, and Dev Ops teams to ensure seamless deployment of AI models. Required Skills & Qualifications: · Bachelor’s or Master’s in Computer Science, Software Engineering, AI, or related field . · 6+ years of experience in software development, AI engineering, or full-stack AI application development . · Strong Python coding skills with experience in frameworks like Fast API, Flask, Django. · Hands-on experience developing APIs for AI models and integrating them into real-world applications. · Experience with LLM APIs (Open AI, Gemini, Claude, Mistral, etc.) and fine-tuning custom models. · Strong knowledge of vector databases (FAISS, Chroma DB, Pinecone) for AI-powered search . · Experience working with Web Sockets, asynchronous programming, and RESTful APIs . · Database experience with Postgre SQL, Mongo DB, or Redis for AI-driven applications. · Experience with MLOps pipelines (MLflow, Airflow, Prefect) for model retraining and monitoring . Good to have Skills & Qualifications: · Familiarity with containerization (Docker, Kubernetes) and cloud-based AI deployments (AWS, GCP, Azure). · Basics of probabilistic models, deep learning techniques, NLP, and embeddings .

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