IN_Sr Associate__Generative AI Engineer_Advisory_Bangalore

V2 Solutions; Hinoba-an; On-site; PHP 1,674,000 - 3,571,000; Full time

Job summary

V2 Solutions in the Philippines is seeking a highly skilled GenAI Engineer to design, develop, and deploy scalable Generative AI solutions using LLMs and transformer architectures. You will build intelligent applications, orchestrate model workflows, and integrate GenAI capabilities into enterprise systems.

You will fine-tune foundation models, develop prompt strategies, implement pipelines with Python, PyTorch, and Hugging Face, and collaborate with data and MLOps teams to productionize models

Qualifications

• Deep expertise in Python and ML frameworks (PyTorch, Transformers).
• Experience building GenAI solutions with LLMs and productivity tools.
• Familiarity with model deployment, CI/CD for ML, and cloud platforms (Azure/AWS/GCP).

Responsibilities

• Design, build, and deploy generative AI solutions using LLMs (OpenAI, Anthropic, Mistral, LLaMA, Falcon).
• Fine-tune foundation models with domain data and techniques.
• Develop prompt engineering strategies for accurate responses.
• Implement model pipelines with Python and ML libraries (PyTorch, Transformers, LangChain).
• Collaborate with data engineers and MLOps to productionize GenAI on cloud platforms.

Skills

Python

PyTorch

Hugging Face Transformers

LangChain

Tools

MLflow

Weights & Biases

Azure ML

SageMaker Pipelines

Job description

Job Summary

We are seeking a highly skilled and innovative GenAI Engineer to join our dynamic team. The ideal candidate will be responsible for designing, developing, and deploying scalable Generative AI solutions using state-of-the-art large language models (LLMs) and transformer architectures. This includes building intelligent applications, orchestrating model workflows, and integrating GenAI capabilities into enterprise systems.

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.
• Agentic AI implementation expertise using C rew.ai or Lang chain.
• Collaborate with data engineers and MLOps teams to productionize GenAI models on cloud platforms (Azure/AWS/GCP).
• Knowledge on Azure/GCP/AWS AI platform like Azure AI Foundry or GCP Vertex.
• Ensure robustness, scalability, and compliance of AI models in deployment environments.
• Good to have experience in finetuning models.
• Good to have experience in SLM.
• Integrate GenAI into enterprise applications via APIs or custom interfaces.
• Evaluate model performance using quantitative and qualitative metrics, and improve outputs through iterative experimentation.

Requirements

• Deep expertise in Python, PyTorch, and Hugging Face Transformers, with hands-on experience deploying solutions on Azure, AWS, or GCP.
• Proficiency in using orchestration frameworks like LangChain.
• Developing APIs with FastAPI or Flask.
• Managing ML pipelines using MLflow or Weights & Biases.
• Familiarity with CI/CD practices for ML, including platforms like Azure ML or SageMaker Pipelines.
• Knowledge on Azure/GCP/AWS AI platforms like Azure AI Foundry or GCP Vertex.