Arivonix - Generative AI Engineer

We are seeking a skilled Generative AI Engineer to design, develop, and deploy AI solutions using Large Language Models (LLMs), multimodal models, vector databases, and AI agents. The ideal candidate should have hands-on experience in building AI-powered applications, optimizing model performance, integrating AI systems into production environments, and staying current with the rapidly evolving GenAI landscape.

Key Responsibilities :

- Design, develop, and deploy GenAI-based solutions using LLMs (e.g., GPT, Llama, Claude, Mistral).

- Build and fine-tune foundation models for application-specific tasks such as:

• Text generation and classification
• Autonomous AI agents
• Retrieval-Augmented Generation (RAG)
• Knowledge Augmented Generation (KAG)
• Chatbots and conversational systems

- Integrate AI models with applications using frameworks such as Lang Chain and Lang graph.

- Develop scalable inference architectures using GPU/CPU compute systems, vector databases, and orchestration frameworks.

- Implement RAG/KAG pipelines using vector stores like Pinecone or Weaviate.

- Work with prompt engineering, evaluation strategies, and quality measurement frameworks.

• - Deploy AI workloads to cloud platforms (AWS, Azure, GCP) using services such as :
• Bedrock, Sage maker, Vertex AI, Azure OpenAI
• Kubernetes, Docker

- Implement data pipelines and manage training datasets for continual improvement.

- Ensure compliance with responsible AI practices, including security, privacy, and hallucination reduction.

- Collaborate with product, UX, and engineering teams to deliver customer-focused AI solutions.

Required Skills & Qualifications :

- Bachelors or Masters degree in Computer Science, Data Science, AI/ML, Engineering, or equivalent.

- Strong programming skills in Python.

- Hands-on experience with :

• LLMs and NLP systems
• KAG and RAG implementations
• Embeddings, vector search, and knowledge indexing

- Experience with AI orchestration tools:

• Lang Chain, Lang graph, or similar

- Familiarity with GPU compute optimization.

- Strong understanding of REST APIs, microservices, and modern backend architecture.

- Experience with cloud platforms such as AWS, GCP, or Azure