Artificial Intelligence Engineer
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Key skills for this role
About the Role
PAAR SYSTEMS AI Engineer Agentic Systems | Model Fine-Tuning | Deep Learning Experience: 3–5 or 5–7 years Type: Full-time Cloud: AWS (required) Role Overview Paar Systems is hiring an AI Engineer to design, build, and productionise advanced AI systems.
Key Skills for This Role
Full Job Posting
Ai Engineer
Agentic Systems | Model Fine-Tuning | Deep Learning
Experience
3–5 or 5–7 years
Role Overview
Paar Systems is hiring an AI Engineer to design, build, and productionise advanced AI systems.
We are looking for candidates with strength in one or more of the focus areas below — agent orchestration, model fine-tuning, or deep learning architecture — and the ability to bridge research and production.
Hands-on AWS experience is required across all profiles.
Agent Orchestration Specialist
Multi-agent system design, memory management, agent debugging and optimisation, and agentic pipeline development.
Knowledge graph / graph RAG experience is expected as a baseline.
Model Fine-Tuning Specialist
Hands-on experience with different fine-tuning approaches (LoRA, full fine-tuning, RLHF, etc.), model evaluation, and adaptation for domain-specific use cases.
Deep Learning Architect
Strong architectural grasp across deep learning systems, ability to design end-to-end ML solutions, and experience bridging research to production.
Key Responsibilities
- Design and develop AI solutions across one or more focus areas — agent orchestration, fine-tuning, or deep learning architecture.
- Build and optimise multi-agent systems, including memory management, agent debugging, and agentic pipeline development.
- Apply knowledge graph / graph RAG techniques to ground and enhance agent reasoning.
- Fine-tune and adapt models using approaches such as LoRA, full fine-tuning, and RLHF for domain-specific use cases.
- Evaluate model performance and iterate on accuracy, reliability, and efficiency.
- Architect end-to-end ML solutions and bridge research prototypes into production-grade systems.
- Deploy, scale, and operate AI workloads on AWS.
- Collaborate with cross-functional teams to translate business needs into AI capabilities.
Required Experience & Skills
- 3–5 years or 5–7 years of relevant AI/ML engineering experience.
- Mandatory hands-on AWS experience (deployment, scaling, and operation of AI/ML workloads).
- Demonstrated strength in at least one focus area: agent orchestration, model fine-tuning, or deep learning architecture.
- Knowledge graph / graph RAG experience expected as a baseline.
- Proficiency with modern ML/AI frameworks and Python.
- Experience taking models and AI systems from research/prototype into production.
Desirable
- Experience across multiple focus areas (agents, fine-tuning, and deep learning architecture).
- Familiarity with vector databases, retrieval pipelines, and LLM tooling/orchestration frameworks.
- Exposure to MLOps practices (CI/CD for models, monitoring, experiment tracking).
- Experience with additional cloud platforms (Azure or GCP).
How To Apply
Submit your resume and a brief summary of a relevant AI/ML project (noting your primary focus area) to Paar Systems at [email protected]
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