Artificial Intelligence Architect

Artificial Intelligence Architect

Role & responsibilities

Key Responsibilities

• AI Architecture & Strategy

• Design and implement enterprise-scale AI architectures leveraging

  LLaMA 3

  and other foundation models.
• Define end-to-end architecture for

  LLM-powered applications

  , including inference, fine-tuning, and deployment pipelines.
• Establish best practices for

  model governance, monitoring, and compliance

  .

• Model Development & Customization

• Lead the

  fine-tuning and instruction-alignment

  of LLaMA 3 for domain-specific use cases (e.g., finance, customs, healthcare, logistics).
• Optimize model performance through

  parameter-efficient fine-tuning (PEFT), quantization, pruning, and RLHF (Reinforcement Learning with Human Feedback)

  .
• Integrate

  vector databases, retrieval-augmented generation (RAG)

  , and multi-modal extensions.

• Infrastructure & Deployment

• Architect and oversee

  distributed training

  on GPU/TPU clusters.
• Deploy scalable inference systems with

  low-latency APIs, containerized environments, and orchestration tools (Kubernetes, Docker, Ray, etc.)

  .
• Implement

  AI DevOps (MLOps)

  practices for continuous integration and delivery of models.

• Cross-Functional Leadership

• Collaborate with data scientists, ML engineers, and software teams to align AI solutions with organizational goals.
  
• Mentor AI engineers in

  LLM fine-tuning, prompt engineering, and model evaluation

  .
• Communicate technical architecture to

  executives and non-technical stakeholders

Preferred candidate profile

Preferred Skills

• Experience with

  agentic AI systems

  and

  multi-agent orchestration

  .
• Contributions to

  open-source AI/LLM projects

  .
• Knowledge of

  blockchain-integrated AI systems

  (smart contracts, decentralized inference).
• Ability to design

  real-time AI copilots and autonomous decision-support systems

  .