Gen ai engineer

Job Summary:We are seeking a highly skilled and experienced Senior Generative AI Engineer to lead the development of intelligent agents powered by advanced generative AI models. In this role, you will be responsible for designing, implementing, and optimizing AI-driven agents that interact naturally with users and systems. You will collaborate with cross-functional teams to bring cutting-edge generative models to life, with a strong emphasis on Python programming, machine learning, and deep learning.Key Responsibilities:• Design, build, and optimize generative AI agents for use in complex applications and workflows.•Develop and fine-tune LLM-based (e.g., GPT, LLa MA, Mistral) agents for autonomous or semi-autonomous decision-making and task execution.• Write robust, scalable Python code to support AI pipelines, model serving, and agent orchestration.• Integrate various ML and deep learning techniques to enhance agent capabilities, including memory, reasoning, and tool usage.• Leverage frameworks such as Lang Chain and Llama Index build and chain agent actions.•Work with structured and unstructured data sources (e.g., text, embeddings, knowledge graphs) to train and inform agents.• Collaborate with product managers, data scientists, and software engineers to deploy agent-based systems into production environments.• Stay updated on the latest research and trends in Gen AI, LLMs, and autonomous agents.Requirements:Must-Have:• 5+ years of experience in software development, with at least 2–3 years in machine learning or deep learning.•Strong proficiency in Python and AI/ML libraries such as Py Torch, Tensor Flow, Hugging Face Transformers, etc.• Experience building or customizing generative models (text generation, summarization, question answering).• Proven experience developing AI agents using frameworks like Lang Chain, Crew AI, Auto Gen, etc.• Solid understanding of LLM architecture, prompt engineering, and retrieval-augmented generation (RAG).• Familiarity with orchestration tools and APIs for tool-use and multi-agent coordination.•Experience with model fine-tuning, embeddings, vector databases (e.g., FAISS, Weaviate), and serving ML models in production.• Strong problem-solving skills, ability to work independently and in a team.Nice-to-Have:•Experience with multi-modal AI (text + vision/audio).• Familiarity with reinforcement learning or human-in-the-loop systems.• Contributions to open-source Gen AI tools or frameworks.•MLOps experience: model deployment, monitoring, and scaling.Tools & Technologies RequiredProgramming & Frameworks:• Python – Primary language for AI development (Required)•Py Torch / Tensor Flow – Deep learning frameworks (Required)• Hugging Face Transformers – For using and fine-tuning LLMs (Required)•Lang Chain / Crew AI / Auto Gen / Haystack – For building LLM-powered agents (Required)LLM & NLP:•Open AI GPT (e.g., GPT-4 / GPT-4o), Anthropic Claude, LLa MA, Mistral, Mixtral, or similar – Familiarity with both proprietary and open-source LLMs (Required)• Prompt engineering and optimization – Crafting and refining system and user prompts (Required)• RAG (Retrieval-Augmented Generation) pipelines (Required)Data & Vector Search:•Vector Databases: FAISS, Weaviate, Pinecone, Chroma (Required)•Embeddings APIs: Open AI, Hugging Face, Cohere (Required)• Oracle DBModel Deployment & MLOps:•Fast API / Flask – For serving models as APIs (Required)•Docker / Kubernetes – Containerization and orchestration (Nice-to-Have)•MLflow / Weights & Biases – Model tracking and experiment management (Nice-to-Have)Orchestration & Tool Use:•Agent Frameworks: Lang Graph, Semantic Kernel, or similar (Required)•Tool Calling APIs: Open AI function calling, Toolformer-like tool integration (Required)Dev Ops & Infrastructure:•Git/Git Hub – Version control (Required)•Cloud platforms: AWS, GCP, Azure – Especially for GPU/TPU access (Nice-to-Have)•CI/CD tools – Git Hub Actions, Jenkins (Nice-to-Have)Other Helpful Tools :•VSCode / Jupyter Notebooks – Development environments (Required)