About the Role
We are looking for an AI Engineer to design, build, and maintain production-grade AI systems across our product and data platforms. You will work at the intersection of large language models, agentic workflows, and scalable MLOps infrastructure, owning end-to-end delivery from data ingestion through to model deployment and monitoring.
In addition, this role includes hands-on responsibility for internal IT infrastructure and end-user computing in a growing team environment.
What You'll Do
AI Engineering & Systems Development
· Design and develop LLM-powered applications including RAG pipelines, prompt engineering systems, and fine-tuned model integrations for production use cases
· Build and maintain multi-agent AI systems using orchestration frameworks (e.g. LangGraph, or equivalent), including tool use, memory management, and agent-to-agent communication
· Construct robust data pipelines for feature engineering, ingestion, transformation, and serving — ensuring data quality and lineage across the ML lifecycle
· Implement and manage MLOps infrastructure including model registries, CI/CD for ML, experiment tracking, and automated retraining workflows
· Deploy and monitor models in cloud environments, establishing observability tooling for latency, drift, and reliability
· Evaluate and integrate third-party AI services, vector databases, and embedding models into production stacks
· Document architectures, conduct code reviews, and contribute to internal engineering best practices
In-house IT & Infrastructure Support
· Manage and maintain internal office IT infrastructure, including network setup, routers, switches, and connectivity troubleshooting
· Implement and monitor data backup strategies (local and cloud) to ensure data integrity, security, and disaster recovery readiness
· Configure and provision user workstations, including OS setup, software installation, access control, and security policies
· Provide technical support to employees on hardware, software, and network-related issues
· Maintain IT documentation, asset inventory, and standard operating procedures for internal systems
· Ensure basic cybersecurity hygiene, including user access management, endpoint protection, patching, and updates
Required Skills
· 2–5 years of hands-on software or ML engineering experience
· Proficiency in Python; familiarity with TypeScript is a plus
· Experience with LLM APIs (Open AI, Anthropic, Gemini) and prompt engineering techniques
· Practical knowledge of RAG architectures and vector databases (e.g. Pinecone, Weaviate, pgvector)
· Exposure to agentic frameworks such as LangChain, LangGraph, or CrewAI
· Solid understanding of ML fundamentals: training, evaluation, fine-tuning, and model drift
· Experience with MLOps tooling: MLflow, Weights & Biases, or equivalent
· Cloud platform experience — AWS, GCP, or Azure (containerisation with Docker/Kubernetes preferred)
· Basic knowledge of IT infrastructure, networking, and end-user system support
Good to Have
· Familiarity with LLM evaluation frameworks (RAGAS, DeepEval, or customevals)
· Knowledge of guardrails, safety filtering, and responsible AI practices
· Experience working in an agile / squad-based delivery model
· Exposure to IT security best practices and backup/recovery systems
Why Krislite (https://www.krislite.com)
Join Krislite, a top player in the lighting industry, and be part of a dynamic, forward-looking team that values initiative, collaboration, and growth. Work alongside experienced colleagues across design, procurement, logistics, and site operations to deliver impactful lighting solutions for our clients.
As a company embracing automation and AI-driven tools, we continuously enhance our processes to work smarter and create better outcomes for our clients and our team. We welcome energetic individuals with a proactive and progressive mindset who are eager to contribute, learn, and grow together with the company.
