IN_Sr Associate__Generative AI Engineer

V2 Solutions; Hinoba-an; On-site; PHP 900,000 - 1,300,000; Full time

Job summary

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

The role involves fine-tuning models, developing prompt strategies, and collaborating with data engineers and MLOps to productionize GenAI on Azure/AWS/GCP. Strong Python and ML framework experience is required.

Qualifications

• Proficiency with orchestration frameworks like LangChain and API development using FastAPI or Flask.

Responsibilities

• Design, build, and deploy generative AI solutions using LLMs.
• Fine-tune and customize foundation models.
• Develop and optimize prompt engineering strategies.
• Implement model pipelines using Python and ML frameworks.
• Collaborate with data engineers and MLOps to productionize GenAI models on cloud platforms.
• Evaluate model performance using metrics and iterate improvements.
• Integrate GenAI into enterprise applications via APIs.
• Ensure robustness, scalability, and compliance of AI models.

Skills

LangChain

FastAPI

Flask

ML pipelines

PyTorch

Transformers

OpenAI

Anthropic

Tools

LangChain

FastAPI

Flask

MLflow

Weights & Biases

PyTorch

Hugging Face Transformers

Azure ML

SageMaker Pipelines

LLaMA

Job description

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

• Proficient in using orchestration frameworks like LangChain, developing APIs with FastAPI or Flask, and managing ML pipelines using tools such as MLflow or Weights & Biases.
• Familiarity with CI/CD practices for ML, including platforms like Azure ML or SageMaker Pipelines, is essential.
• Knowledge on Azure/GCP/AWS AI platform like Azure AI Foundry or GCP Vertex.