Design, develop, and maintain large-language-model (LLM) driven solutions with strong Python, cloud infrastructure, and production-scale best practices. Lead or participate in prompt engineering, fine-tuning, evaluation, and deployment of LLMs. Build scalable backend services and deploy cloud infrastructure supporting AI/ML workloads.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
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