Generative AI Engineer

Company Description

Versavvy Limited is an independent Nigerian technology solutions company focused on building practical, high-impact digital products and enterprise solutions. Our work spans artificial intelligence, software engineering, data engineering, cloud solutions, and automation. We design and deliver secure, reliable, and user-focused systems that help organizations solve real business problems, improve efficiency, and scale intelligently.

Role Description

Versavvy Limited is hiring a Generative AI Engineer for a full-time, on-site role in Lagos.

This role is for an engineer who can do more than talk about AI. We are looking for someone who has actually built, tested, and deployed real AI solutions, especially solutions involving large language models, NLP, retrieval systems, intelligent automation, or other applied generative AI use cases.

The Generative AI Engineer will be responsible for designing, building, testing, and improving AI-powered applications and services that solve practical business problems. This includes working on LLM-based systems, prompt and workflow design, data preparation, model evaluation, performance optimization, and production deployment. The engineer will work closely with product, engineering, and business teams to deliver solutions that are accurate, reliable, scalable, and aligned with business goals.

This is a hands-on execution role. We are specifically looking for candidates with strong implementation skills, not just academic exposure or theoretical knowledge.

Qualifications

• Design, build, and optimize generative AI applications for real world business use cases
• Develop LLM-powered features such as chat assistants, document intelligence, summarization, search, classification, extraction, or workflow automation
• Build and improve pipelines for prompt engineering, retrieval augmented generation, evaluation, fine-tuning, and model monitoring where needed
• Prepare, clean, structure, and analyze datasets for AI application development
• Integrate AI services into production-ready applications and internal systems
• Evaluate model performance using practical quality, accuracy, latency, and reliability metrics
• Work with software engineers, product teams, and stakeholders to translate business needs into working AI solutions
• Stay current with advancements in generative AI, LLM tooling, model serving, and AI engineering best practices
• Contribute to code quality, documentation, testing, and deployment standards

Required Qualifications

Applicants will only be considered if they demonstrate clear, practical, hands-on experience in the following areas:

• Strong Python programming skills with the ability to build production grade applications
• Solid experience in machine learning, deep learning, and natural language processing
• Practical experience building with modern AI frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, or similar tools
• Experience working with large language models, prompt engineering, retrieval workflows, embeddings, vector databases, or related generative AI systems
• Good understanding of data preprocessing, feature preparation, model evaluation, and performance tuning
• Experience deploying AI or ML solutions on cloud platforms such as AWS, Azure, or Google Cloud
• Ability to write clean, maintainable, well documented code
• Strong problem solving ability and the discipline to test and validate outputs properly
• Ability to work effectively in a collaborative, fast moving engineering environment
• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a closely related field

Preferred Qualifications

Candidates with the following will stand out strongly:

• Prior industry experience building and shipping generative AI applications
• Experience with RAG pipelines, vector databases, model evaluation frameworks, or agent based workflows
• Experience integrating AI into enterprise systems, internal tools, or customer facing products
• Familiarity with API development, backend engineering, Docker, and production deployment workflows
• Experience working with cloud infrastructure, CI/CD pipelines, and monitoring of AI applications
• A portfolio, GitHub repository, case study, or demonstrable project showing real work completed