GenAI Application Engineer: Python, LLMs & Cloud

SIRO Clinpharm Pvt. Ltd.; United States; Teletrabalho; USD 120 000 - 170 000; Tempo integral

Resumo da oferta

SIRO Clinpharm Pvt. Ltd. is seeking a GenAI Application Developer (Python) with 7-10 years of experience to design and deploy enterprise GenAI applications. The role focuses on Python, FastAPI, LLMs, RAG, vector databases, and AWS cloud, delivering scalable APIs and microservices.

You will integrate LLMs across OpenAI, Azure OpenAI, AWS Bedrock, or Vertex AI and drive cloud-native deployment with containerized architectures, collaborating with cross-functional teams.

Qualificações

• Strong expertise in Python, FastAPI, LLMs, RAG and vector databases.
• Experience designing enterprise GenAI apps on cloud platforms (AWS, Azure, GCP).
• Ability to build scalable REST APIs and microservices.

Responsabilidades

• Design and develop enterprise GenAI applications using Python and FastAPI.
• Integrate LLMs via OpenAI, Azure OpenAI, AWS Bedrock or Vertex AI.
• Develop RAG solutions with document ingestion, embedding, and semantic search.
• Build scalable REST APIs and microservices for AI-powered apps.
• Deploy containerized apps with Docker and Kubernetes.
• Develop and optimize vector database and enterprise search capabilities.
• Implement CI/CD and cloud-native deployment strategies.
• Collaborate with architects and product teams to deliver AI solutions.

Conhecimentos

Python

FastAPI

LLMs

RAG

Vector Databases

AWS Cloud

REST APIs

Microservices

CI/CD

Ferramentas

Docker

Kubernetes

ECS

EKS

OpenAI

Azure OpenAI

AWS Bedrock

Vertex AI

Descrição da oferta de emprego

SIRO Clinpharm Pvt. Ltd. is seeking a GenAI Application Developer (Python) with 7-10 years of experience to design and deploy enterprise GenAI applications. The role focuses on Python, FastAPI, LLMs, RAG, vector databases, and AWS cloud, delivering scalable APIs and microservices.

You will integrate LLMs across OpenAI, Azure OpenAI, AWS Bedrock, or Vertex AI and drive cloud-native deployment with containerized architectures, collaborating with cross-functional teams.