Neova Solutions - Generative AI Developer

About Neova :

Neova Solutions is a product specialist based at Santa Clara, California and Pune, India as the development center. We are a 18-years-old IT organization. We deliver next-gen solutions for leading US-based product companies such as Redwood, Stanley, Sysdig, Proofpoint, Nextiva, Shooter Detection Systems, Sdx Central and more.

Our service offerings include generative AI solutions, workload automation software products, cloud security solutions, IoT solutions, innovative solutions for public safety and security and data-as-a-service products such as Data Mart and so on.

We hire, empower and retain a diverse workforce within a supportive work environment to deliver high-quality technology solutions that enable our clients to meet their business goals effectively.

Please visit our website https : 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, Llama.cpp, 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, llama.cpp, 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 :

(ref : hirist.tech)