
Gen AI Developer
2 days ago
Role: Gen AI Developer
Total Experience: 6+ years in development with 2+ years in Gen AI development
Employment Type: Permanent & full time
Working Model: Hybrid (3 days work from office)
Job Summary:
We are seeking a Senior AI Developer with proven expertise in Generative AI technologies, a solid foundation in machine learning, and a strong understanding of data governance. The ideal candidate will have hands-on experience with both cloud-based LLM platforms, on-premise, open-source LLMs like Ollama, , and GGUF-based models. You should also have good knowledge in Model Context Protocol (MCP). You will help architect and implement GenAI-powered products that are secure, scalable, and enterprise-ready.
Key Responsibilities:
- Design, build, and deploy GenAI solutions using both cloud-hosted and on-prem LLMs.
- Work with frameworks like Hugging Face, LangChain, LangGraph, LlamaIndex to enable RAG and prompt orchestration.
- Implement private LLM deployments using tools such as Ollama, LM Studio, , GPT4All, and vLLM.
- Design retrieval-augmented generation (RAG) pipelines with context-aware orchestration using MCP.
- Implement and manage Model Context Protocol (MCP) for dynamic context injection, chaining, memory management, and secure prompt orchestration across GenAI workflows.
- Fine-tune open-source models for specific enterprise tasks and optimize inference performance.
- Integrate LLMs into real-world applications via REST, gRPC, or local APIs.
- Ensure secure data flows and proper context management in RAG pipelines.
- Collaborate across data, product, and infrastructure teams to operationalize GenAI.
- Incorporate data governance and responsible AI practices from design through deployment.
Required Skills and Qualifications:
- 6+ years of experience in AI/ML; 2+ years working on GenAI initiatives.
- Solid understanding of object-oriented programming and software design principles.
- Experience working with at least one Generative AI framework (e.g., OpenAI, Hugging Face, Stable Diffusion).
- Familiarity with ML libraries such as TensorFlow, PyTorch, or Transformers.
- Experience with REST APIs, databases (SQL/NoSQL), and version control (Git).
- Strong problem-solving and communication skills.
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