Generative AI Engineer

4 days ago

Greater Hyderabad Area, 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 GenAI models (FastAPI, 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, LLaMA, Gemini, Claude, Mistral) for performance in real-time applications.

· Develop AI-powered chatbots, document extraction tools, and automation systems using LangChain, Haystack, or Semantic Kernel.

· Implement vector search using FAISS, ChromaDB, or Pinecone for retrieval-augmented generation (RAG) applications.

· Work with databases (PostgreSQL, MongoDB, Redis) to manage AI-driven data workflows.

· Build scalable AI microservices and integrate them into enterprise applications.

· Collaborate with backend engineers, data engineers, and DevOps 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 FastAPI, Flask, Django.

· Hands-on experience developing APIs for AI models and integrating them into real-world applications.

· Experience with LLM APIs (OpenAI, Gemini, Claude, Mistral, etc.) and fine-tuning custom models.

· Strong knowledge of vector databases (FAISS, ChromaDB, Pinecone) for AI-powered search.

· Experience working with WebSockets, asynchronous programming, and RESTful APIs.

· Database experience with PostgreSQL, MongoDB, 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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