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GenAI Developer at Weekday AI

Bhopal, Madhya Pradesh, India -

Full Time

Start Date

Immediate

Expiry Date

09 Feb, 26

Salary

2100000.0

Posted On

11 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, AWS, Docker, Kubernetes, LLMs, Prompt Engineering, Microservices, MLOps, Vector Databases, Agent Frameworks

Industry

technology;Information and Internet

Description

This role is for one of the Weekday's clients Salary range: Rs 1200000 - Rs 2100000 (ie INR 12-21 LPA) Min Experience: 6 years Location: Jaipur, Bhopal, Pune, Gurgaon, Bangalore, Chennai JobType: Contract - Onsite Opportunity We’re looking for a GenAI Developer to design, develop, and deploy advanced Generative AI solutions leveraging modern AI frameworks and AWS services. This role involves building and fine-tuning large language models (LLMs), developing intelligent AI agents, and implementing scalable, secure, and high-performance GenAI architectures for enterprise use cases. Key Responsibilities Design, develop, and deploy Generative AI solutions using modern AI frameworks and AWS cloud services. Build, fine-tune, and optimize LLMs tailored for enterprise applications. Develop and integrate AI agents using Python and agent-based AI frameworks. Implement end-to-end GenAI pipelines leveraging AWS Bedrock, SageMaker, Lambda, and API Gateway. Lead proof-of-concept (POC) initiatives and scale production-grade GenAI systems. Ensure performance, scalability, and security of AI-driven applications. Required Skills Programming: Python Cloud & AI Services: AWS (Bedrock, SageMaker, EC2, Lambda, S3) AI & ML Tools: Agent frameworks, LLMs, Prompt Engineering Databases: Vector Databases (Pinecone, FAISS, Weaviate) Architecture & Infrastructure: Microservices, Docker, Kubernetes, MLOps Core Skills Python | AWS | Docker | Kubernetes

Responsibilities

The GenAI Developer will design, develop, and deploy advanced Generative AI solutions using modern AI frameworks and AWS services. This includes building and fine-tuning large language models and implementing scalable GenAI architectures for enterprise applications.