emerchantpay

AI Engineer

• Design, build, and maintain AI-powered applications, services, and integrations as part of the AI Engineering team.
• Implement solutions focused on AI agents, agentic workflows, automation, LLM-based applications, and AI-assisted business processes.
• Build and integrate AI applications using technologies such as Python (FastAPI/Flask/Django) or equivalent frameworks, React frontends, and relevant AI/ML frameworks.
• Implement AI solutions using AWS AI/ML services, including Amazon Bedrock, Amazon Bedrock AgentCore, Amazon SageMaker, and other AWS services for model hosting, inference, orchestration, data processing, monitoring, and security.
• Work closely with the AI Tech Lead to align on architecture, technology choices, engineering standards, AI patterns, and rollout approaches.
• Provide technical input and guidance to other engineers on AI implementation patterns, code quality, testing, observability, and production readiness.
• Develop and integrate AI agents that interact with internal APIs, business workflows, enterprise systems, knowledge bases, and external tools in a safe and controlled way.
• Build and maintain RAG-based solutions, including document ingestion, chunking, embeddings, vector search, retrieval logic, reranking, and grounding techniques.
• Support the development and deployment of machine learning models and AI solutions into production environments.
• Contribute to ML pipelines and MLOps practices, including data preparation, model training, experiment tracking, model deployment, monitoring, evaluation, and lifecycle management.
• Integrate LLMs through APIs.
• Implement AI evaluation approaches for LLM outputs, RAG quality, agent behavior, model performance, hallucination detection, safety, and reliability.
• Support prompt engineering, prompt versioning, function calling, tool use, memory patterns, guardrails, and LLM application testing.
• Design and consume APIs and contribute to cloud-based, scalable backend architectures.
• Collaborate with product managers, engineers, data scientists, DevOps, security, and business stakeholders to deliver practical AI solutions.
• Write clean, maintainable, testable, and well-documented code.
• Support production rollouts, troubleshooting, monitoring, optimization, and continuous improvement of AI systems.
• Stay current with modern AI technologies, frameworks, models, and engineering practices, and bring practical recommendations to the team.

Senior AI Engineer

Learning and Development

• Develop e-learning training content in different topics.
• Maintain and upgrade company orientation training.
• Partner with subject matter experts to ensure all training content is up to date.
• Partner with stake holders to ensure learning needs across global locations are anticipated and met.
• Build and maintain meaningful relationships with stake holders across the organisation.
• Use different tools and methods for training planning, creation and execution.
• Deliver training in various formats (webinars/workshops/online/live).
• Create and follow various reports on training success.
• Drive learners’ engagement through different training initiatives.
• Collaborate proactively with the team on fostering a learning culture environment.

Senior AI Engineer

Training Specialist