Senior Associate GEN AI Engineer

Role Overview: At PwC, as a GenAI Engineer, you will be part of a dynamic team focusing on designing, developing, and deploying scalable Generative AI solutions using state-of-the-art large language models (LLMs) and transformer architectures. Your role will involve building intelligent applications, orchestrating model workflows, and integrating GenAI capabilities into enterprise systems. The position requires deep expertise in Python, PyTorch, and Hugging Face Transformers, along with hands-on experience in deploying solutions on cloud platforms such as Azure, AWS, or GCP. Collaboration with data engineers and MLOps teams to ensure the robustness, scalability, and compliance of AI models in deployment environments is crucial. Keeping up to date with the latest research in GenAI and relevant open-source tools will also be an essential aspect of your role. Key Responsibilities: - Design, build, and deploy generative AI solutions using LLMs such as OpenAI, Anthropic, Mistral, or open-source models (e.g., LLaMA, Falcon). - Fine-tune and customize foundation models using domain-specific datasets and techniques. - Develop and optimize prompt engineering strategies to drive accurate and context-aware model responses. - Implement model pipelines using Python and ML frameworks such as PyTorch, Hugging Face Transformers, or LangChain. - Collaborate with data engineers and MLOps teams to productionize GenAI models on cloud platforms (Azure/AWS/GCP). - Integrate GenAI into enterprise applications via APIs or custom interfaces. - Evaluate model performance using quantitative and qualitative metrics, and improve outputs through iterative experimentation. - Keep up to date with the latest research in GenAI, foundation models, and relevant open-source tools. Qualifications Required: - 3 to 5 years of experience in Generative AI (LLMs, Transformers), Python, PyTorch, Hugging Face Transformers, Azure/AWS/GCP cloud platforms, LangChain/Langgraph or similar orchestration frameworks, REST APIs, FastAPI, Flask, ML pipeline tools (MLflow, Weights & Biases), Git, CI/CD for ML (e.g., Azure ML, SageMaker pipelines). - Education qualification: B.E/B.Tech/M.Tech/MCA. - Degrees/Field of Study required: MBA (Master of Business Administration). Additional Company Details: At PwC, you will be part of a vibrant community that values trust and creates distinctive outcomes for clients and communities. The purpose-led and values-driven work, fueled by technology and innovation, will enable you to make a tangible impact in the real world. PwC provides equal employment opportunities and fosters an environment where each individual can contribute to their personal growth and the firm's growth without facing discrimination based on various factors. Zero tolerance is maintained for any discrimination or harassment in the workplace. Role Overview: At PwC, as a GenAI Engineer, you will be part of a dynamic team focusing on designing, developing, and deploying scalable Generative AI solutions using state-of-the-art large language models (LLMs) and transformer architectures. Your role will involve building intelligent applications, orchestrating model workflows, and integrating GenAI capabilities into enterprise systems. The position requires deep expertise in Python, PyTorch, and Hugging Face Transformers, along with hands-on experience in deploying solutions on cloud platforms such as Azure, AWS, or GCP. Collaboration with data engineers and MLOps teams to ensure the robustness, scalability, and compliance of AI models in deployment environments is crucial. Keeping up to date with the latest research in GenAI and relevant open-source tools will also be an essential aspect of your role. Key Responsibilities: - Design, build, and deploy generative AI solutions using LLMs such as OpenAI, Anthropic, Mistral, or open-source models (e.g., LLaMA, Falcon). - Fine-tune and customize foundation models using domain-specific datasets and techniques. - Develop and optimize prompt engineering strategies to drive accurate and context-aware model responses. - Implement model pipelines using Python and ML frameworks such as PyTorch, Hugging Face Transformers, or LangChain. - Collaborate with data engineers and MLOps teams to productionize GenAI models on cloud platforms (Azure/AWS/GCP). - Integrate GenAI into enterprise applications via APIs or custom interfaces. - Evaluate model performance using quantitative and qualitative metrics, and improve outputs through iterative experimentation. - Keep up to date with the latest research in GenAI, foundation models, and relevant open-source tools. Qualifications Required: - 3 to 5 years of experience in Generative AI (LLMs, Transformers), Python, PyTorch, Hugging Face Transformers, Azure/AWS/GCP cloud platforms, LangChain/Langgraph or similar orchestration frameworks, REST APIs, FastAPI, Flask, ML pipeline tools (MLflow, Weights & Biases), Git, CI/CD for ML (e.g., Azure ML, SageMaker pipelines). - Education qualific