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