GenAI Developer

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a GenAI Developer - Fractional in India.

In this role, you will lead the design, development, and deployment of cutting-edge Generative AI solutions, building systems that integrate Large Language Models (LLMs), vector databases, and cloud AI services. You will be responsible for architecting scalable, high-performance AI pipelines, optimizing models for efficiency, and enabling robust MLOps workflows. This position requires close collaboration with cross-functional teams to ensure solutions meet business objectives while staying at the forefront of AI innovation. The ideal candidate thrives in a remote, fast-paced environment, has deep technical expertise in Python and AI frameworks, and enjoys translating complex AI concepts into tangible business impact.

· Lead the architecture and design of advanced Generative AI systems, including LLM selection, fine-tuning, and RAG pipeline implementation.

· Develop scalable solutions leveraging cloud AI platforms (Azure AI, AWS Bedrock) and open-source frameworks such as LangChain and LlamaIndex.

· Optimize models and systems for performance, cost-efficiency, and scalability, using techniques like prompt engineering and model quantization.

· Implement and manage vector database solutions (e.g., Pinecone, Weaviate, Chroma) to support similarity search in AI applications.

· Establish robust MLOps pipelines, including CI/CD, containerization, and automated deployment of GenAI models.

· Provide technical leadership, mentoring, and guidance on GenAI best practices to development teams.

· Collaborate with stakeholders to align AI solutions with business goals and effectively communicate complex technical concepts to non-technical audiences.

· Proven expertise in Generative AI, including LLMs, Transformers, Diffusion Models, and RAG architectures.

· Strong experience with AI frameworks such as LangChain, LlamaIndex, Hugging Face, TensorFlow, and PyTorch.

· Proficiency in cloud AI platforms (Azure AI, AWS Bedrock, Google Vertex AI) and vector databases (Pinecone, Weaviate, Chroma, Milvus).

· Hands-on experience in MLOps practices, including CI/CD pipelines, Docker, Kubernetes, and Azure DevOps.

· Expert-level programming skills in Python and experience developing RESTful APIs.

· Knowledge of data engineering concepts, pipelines, and cloud data services.

· Familiarity with solution architecture, microservices, design patterns, and scalable cloud systems.

· Certifications in AI/ML platforms (Azure AI Engineer Associate, AWS Certified Machine Learning – Specialty) are a plus.

· Strong problem-solving skills, technical leadership, and ability to communicate complex AI concepts to diverse stakeholders.

· Fully remote work with flexible hours.

· Opportunity to work on cutting-edge AI technology and influence AI adoption in business applications.

· Exposure to cloud AI platforms, open-source frameworks, and large-scale GenAI systems.

· Professional development through access to AI research, certifications, and industry trends.

· Collaborative, innovation-driven work environment with cross-functional teams.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.

Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
It compares your profile to the job's core requirements and past success factors to determine your match score.
Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias, focusing solely on your fit for the role.
Once the shortlist is completed, it is shared directly with the company that owns the job opening. The final decision and next steps (such as interviews or assessments) are then managed by their internal hiring team.

Thank you for your interest

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