Senior AI Developer / AI Architect

We are seeking AI Developers / AI Architects (FULL TIME) and building a team exclusively to support our global client on a fully remote contract basis.

Contract Length: 6 Months (Renewable)

Contract Type: Full Time – Contractor

Location: Remote

The role focuses on designing, deploying and maintaining large-language-model (LLM) driven solutions with strong Python, cloud infrastructure (AWS preferred), and production-scale best practices. You’ll work across prompt engineering, RAG (retrieval-augmented generation), LLM fine-tuning, API/microservices integration, and end-to-end delivery of AI/GenAI features in live applications.

• Design, develop and integrate LLM-based applications and services using Python.
• Lead or participate in prompt engineering, fine-tuning, evaluation and deployment of LLMs (OpenAI, Hugging Face, custom models).
• Build scalable backend services (APIs/microservices) to support GenAI and LLM workflows, ensuring robustness, performance and scalability.
• Deploy and maintain cloud infrastructure (preferably AWS) supporting AI/ML workloads, containers/servers, model-deployment pipelines.
• Work with data scientists, engineers and product teams to translate business use-cases into technical AI/LLM solutions.
• Implement monitoring, logging, metrics, and SLOs around AI/LLM systems (latency, accuracy, drift, etc).
• Stay current with AI/ML/LLM research, frameworks and best-practices and introduce innovations into the stack.
• Mentor junior engineers, set standards for AI code, pipelines, architectures.

• 5+ years of software engineering experience (Python - must) AND at least 2-3 years working specifically on LLM or GenAI projects.
• Strong proficiency in Python, and experience with ML/AI libraries (PyTorch, TensorFlow, Hugging Face).
• Solid understanding of backend API/microservice architecture.
• Hands-on experience with large language models (LLMs), prompt engineering, RAG and fine-tuning.
• Experience building and operating scalable cloud-native services (AWS preferred) for AI workloads.
• Excellent problem-solving skills, initiative, and ability to work independently in a hybrid/remote environment.
• Clear communication skills and ability to engage with both technical and business stakeholders.

• Experience with containerisation (Docker, Kubernetes) and orchestration of AI services.
• Familiarity with Infrastructure as Code (Terraform, AWS CDK) for deploying AI infrastructure.
• Knowledge of agentic AI workflows