A.I. Lab Engineer

MC Systems

About JN:

We are The Jamaica National Group Limited, representing a globally respected brand, boldly finding ways to enrich lives and build better communities. Our core values make us who we are and are demonstrated in everything we do; rooted in RESPECT we believe our everyday jobs contribute to something bigger than ourselves. We are dependable and pride ourselves in our authenticity and in the transparent solutions we create that bring value to our customers.

About MC Systems:

MC Systems Limited, a subsidiary of the Jamaica National Group, has been delivering innovative ICT products and services to global markets since 1973. We leverage emerging technologies, deep industry expertise and a culture of innovation to develop solutions that create meaningful value for our customers and stakeholders.

Job Summary:

Reporting directly to the A.I. Lab and Deployment Lead, the  A.I. Lab Engineer  will be responsible for designing, building, and operationalizing A.I. and agentic solutions that power the company's Artificial Intelligence Centre of Excellence.

The successful candidate will transform prioritized business use cases into secure, scalable and production-ready solutions, taking initiatives from rapid prototyping and experimentation through to deployment and integration within the JN Group's enterprise platforms and systems.

Key Responsibilities

A.I. Solution Development & Engineering

• Design, build and iterate on A.I. and agentic solutions that address prioritized business use cases.
• Develop and maintain clean, scalable, production-grade code and reusable components for the lab's shared toolkit.
• Rapidly prototype and conduct structured experiments to validate concepts and transform successful prototypes into robust enterprise solutions.
• Contribute to the development of proprietary models, prompt libraries, retrieval pipelines and agent workflows.

Agentic A.I. & Model Implementation

• Implement autonomous and multi-agent workflows using modern LLM and agent frameworks, including tool usage, orchestration and human-in-the-loop controls.
• Build Retrieval-Augmented Generation (RAG) pipelines, including data ingestion, chunking, embeddings and vector search capabilities.
• Develop evaluation frameworks, test datasets, and guardrails to assess and monitor model behaviour before and after deployment.

Deployment, MLOps & Integration

• Package, deploy, and monitor A.I. services while integrating them with enterprise systems and APIs across the JN Group technology landscape.
• Build and maintain CI/CD pipelines, containerized workloads and MLOps tooling to support repeatable and auditable releases.
• Implement logging, monitoring and observability practices to track performance, cost, latency and model drift in production environments.
• Ensure compliance with A.I. governance, security, data privacy and risk management standards throughout the solution lifecycle.

Collaboration & Continuous Learning

• Partner closely with internal stakeholders to gather requirements, demonstrate working solutions and deliver end-to-end A.I. solutions.
• Develop and maintain technical documentation, architectural diagrams, operational runbooks and knowledge repositories.
• Remain current on advancements in A.I., machine learning and agentic systems, introducing relevant innovations into the lab.

Qualifications & Experience

The ideal candidate should possess:

• Bachelor's degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, or a related field. A Master's degree is an asset
• Minimum of two (2) years' hands-on experience in software engineering or A.I./ML engineering, with demonstrated delivery of working solutions
• Practical experience developing applications using Large Language Models (LLMs), agentic frameworks, or machine learning technologies, including at least one solution deployed to production or pilot
• Experience within enterprise or financial services environments would be advantageous
• Strong proficiency in Python and solid software engineering fundamentals, including version control, testing and code reviews
• Hands-on experience with frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent technologies
• Experience with RAG architectures, embeddings, and vector databases such as Pinecone, Weaviate, pgvector, or similar platforms
• Familiarity with A.I. and ML frameworks including PyTorch, TensorFlow, Scikit-learn, and Hugging Face
• Experience working with cloud platforms (AWS, Azure, or GCP), Docker containers, CI/CD pipelines, and MLOps practices
• Sound understanding of APIs, SQL, systems integration and data engineering fundamentals
• Strong analytical, problem-solving and solution-delivery capabilities
• Excellent written and verbal communication skills, with the ability to explain technical concepts to both technical and non-technical audiences
• Demonstrated commitment to security, quality and responsible A.I. practices within regulated environments
• Ability to work independently while collaborating effectively within a fast-paced innovation environment.

A.I. Assisted Software Development Experience

• Proven experience using A.I. coding assistants and agents such as Cursor, GitHub Copilot, Codex, Claude Code, or similar tools
• Ability to design and maintain repository context, memory files, coding standards and linting frameworks that influence agent outputs
• Strong code review and quality assurance discipline, with the ability to identify architectural issues, security vulnerabilities and logic defects in A.I. generated code
• Experience designing A.I. assisted development workflows, including appropriate delegation to A.I. agents and orchestration across multiple tools
• Excellent debugging, troubleshooting and root-cause analysis skills.

What Success Looks Like

Success in this role will be demonstrated through:

• Delivery of high-quality A.I. and agentic solutions that satisfy business requirements and project timelines.
• Successful deployment of impactful A.I. solutions into pilot or production environments with measurable business outcomes.
• Development of reusable components, pipelines, frameworks and evaluation tooling that improve lab productivity.
• Adherence to governance, security, compliance and responsible A.I. standards.
• Effective collaboration, knowledge sharing and contribution to the growth of the A.I. Centre of Excellence.

Technical Areas of Focus

The successful candidate should possess strong knowledge and practical experience in the following areas:

• Applied Machine Learning
• Generative A.I. and Large Language Models (LLMs)
• Agentic A.I. and Multi-Agent Systems
• Retrieval-Augmented Generation (RAG)
• Prompt Engineering
• Model Evaluation and Optimization
• Cloud Computing and A.I. Infrastructure
• Containerization and MLOps
• Data Engineering
• API Development and Integration

Why Join MC Systems?

Join a high-performing technology organization where innovation meets impact. This is a unique opportunity to help shape the future of A.I. driven solutions across the Caribbean while contributing to transformative products and services for financial institutions and businesses.

MC Systems offers a competitive compensation package, a collaborative and dynamic work environment and opportunities for professional growth, learning and career advancement.

Application Deadline: Sunday, September 6, 2026