Senior AI Engineer

base camp digital pte. ltd.

Singapore

On-site

SGD 180,000 - 280,000

Full time

3 days ago
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Job summary

Base Camp Digital Pte. Ltd. invites Senior AI Engineers to own AI outcomes end-to-end, architecting and delivering AI solutions, then evaluating model performance with real users. We’re building something new to make government interactions simpler and more valuable for businesses.

You’ll tune and scale generative models, deploy AI products on cloud platforms, and address failure modes while balancing cost, latency and reliability to deliver value for businesses.

Qualifications

  • Advanced degree in computer science, data science, NLP, ML or deep learning.
  • 8+ years of experience.
  • Experience fine-tuning and scaling generative AI models, with strong knowledge of transformer-based LLMs, RLHF and fine-tuning at inference scale.
  • Experience deploying and scaling AI products in production on AWS, GCP or Azure.
  • Working knowledge of RAG, knowledge graphs, context engineering and prompt engineering.
  • Experience building evaluations and guardrails for agentic AI.
  • Experience with AI protocols (MCP, AG-UI, A2A, A2UI, etc.).
  • Experience architecting a scalable AI tooling ecosystem.

Responsibilities

  • Customer-obsessed: talk directly to users to find where models fall short.
  • Outcome-driven: judge success by task completion, accuracy, latency and cost per inference.
  • Decisive and iterative: make clear calls under ambiguity and ship to generate signal.
  • Domain expert: scale AI products and design for failure modes like hallucination and latency under load.
  • Commercially aware: balance cost, latency and reliability as product constraints.
  • A force multiplier: document decisions and communicate limitations clearly.
  • Optimistic problem-solver: treat failures as engineering problems with tractable solutions.

Skills

AI model fine-tuning
LLM deployment
Production-scale ML
Prompt engineering

Education

Advanced degree in computer science, data science, NLP, ML or deep learning

Tools

AWS
GCP
Azure

Job description

Job Summary

We’re hiring Senior AI Engineers who combine deep AI expertise with strong product instinct. You’ll own AI outcomes end-to-end: architecting and delivering AI solutions, then evaluating and optimising model performance in the hands of real users. We’re building something new to make government interactions simpler and more valuable for businesses.

Job Responsibilities
  • Customer-obsessed: You talk directly to users (businessowners, accountants, agency officers) to find where models fall short in ways benchmarks miss.
  • Outcome-driven: You judge success by task completion, accuracy, latency and cost per inference, not architectural elegance.
  • Decisive and iterative: You make clear calls under ambiguity, ship to generate signal, instrument everything, and close the loop quickly.
  • Domain expert: You’ve scaled AI products in production and design for LLM failure modes such as hallucination, context degradation, prompt injection and latency under load.
  • Commercially aware: You treat cost, latency and reliability as product constraints and can articulate tradeoffs clearly.
  • A force multiplier: You make AI systems legible to PMs, engineers and analysts through clear documentation, decision records and honest communication of limitations.
  • Optimistic problem-solver: You treat failures and constraints as engineering problems with tractable solutions.
Job Requirements
  • Advanced degree in computer science, data science, NLP, ML or deep learning
  • 8+ years of experience
  • Experience fine-tuning and scaling generative AI models, with strong knowledge of transformer-based LLMs, RLHF and fine-tuning at inference scale
  • Experience deploying and scaling AI products in production on AWS, GCP or Azure
  • Working knowledge of RAG, knowledge graphs, context engineering and prompt engineering
  • Experience building evaluations and guardrails for agentic AI
  • Experience with AI protocols (MCP, AG-UI, A2A, A2UI, etc.)
  • Experience architecting a scalable AI tooling ecosystem
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