Your career compass awaits
Create a free account to unlock
- ✓ See how you match this role
- ✓ AI resume tailored to this specific job
- ✓ Inside Track Companion — find your insider contact
- ✓ Skills gap analysis and upskill plan
- ✓ Interview prep kit for this role
- ✓ Relocation concierge — salary, tax, cost of living
Free — no credit card required
LLM Application Engineer
ICT
💰 Salary Not shared
📊 Market S$10,000–S$18,000/mo (S$120,000–S$216,000/yr)
About the Company
About ActAI There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting. We aim to bring intelligence to conversations, errands, organising and workflows, with minimal to no prompting. Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. We believe products will greatly reduce hallucinations. Our objective is to organise anyone's life, allowing us all to spend time on valuable and meaningful things.
About the Role
As an LLM Application Engineer, you will build the intelligence layer that powers ActAI's AI experiences.
Responsibilities
- ● esigning agent workflows, improving model behaviour, and turning AI capabilities into reliable user experiences.
- ● You will own problems end-to-end, from understanding user needs, designing Agentic workflows, integrating models and tools, building evaluation system and continuously improving AI behaviour in production.
- ● Build and ship LLM-powered applications and AI agent workflows
- ● Design systems for reasoning, planning, memory, tool uuse and multi-step execution
- ● Build reliable orchestration pipelines that turn probabilistic model outputs into predictable, observable, and safe actions
- ● Integrate LLMs with APIs, databases, search, internal services, and external tools.
- ● Develop prompting, context engineering, structured outputs, tool-calling, and other techniques to improve model behaviour
- ● Build evaluation frameworks and datasets to measure AI quality, reliability, and regressions
- ● Debug AI systems across the entire stack-from model behaviour and prompts to orchestration, backend services, and product UX
- ● Optimise AI systems for quality, latency, and cost
- ● Work closely with product and engineering teams to turn ambiguous product problems into working AI solutions
- ● Establish production practices for observability, tracing, experimentation, evaluation, and continuous improvement
- ● LLM APIs and model providers, including OpenAI-compatible APIs and open-weight models
- ● Agent frameworks and orchestration systems
- ● Vector databases and retrieval systems
- ● Backend services, APIs, and distributed systems
- ● PyTorch / JAX
- ● Ideal Experience
- ● Strong software engineering fundamentals with experience building AI-powered applications
- ● Hands-on experience with LLMs, generative AI, or agent-based systems
Confirm Application
Are you applying to ?
We'll track this in your dashboard as Applied.
Saving to your tracker…
Stand out: message someone at BJAK.
A short, personal note to a recruiter can get your application looked at sooner.
⚡ Full Resume Sandbox Canvas