AI Engineer

ai32; Daerah Khusus Ibukota Jakarta; On-site; IDR 180,000,000 - 320,000,000; Full time

Job summary

ai32 is seeking an AI Engineer to lead the AI layer of our product in Jakarta. You will design architectures, implement scalable AI systems, and work across product and engineering to deliver production-ready AI capabilities.

You will focus on improving answer quality, latency, reliability, and cost, while ensuring security and privacy through guardrails and robust execution practices. The role requires independent work and strong technical decision-making.

Qualifications

• Strong proficiency in Python and asynchronous services.
• Experience developing AI agents, workflows, tool calling, MCP, structured outputs, state, and memory.
• Solid understanding of Retrieval-Augmented Generation (RAG), embeddings, retrieval, reranking, and source grounding.
• Hands-on experience with Amazon Bedrock and AgentCore.

Responsibilities

• Design and Develop AI Solutions: Translate business requirements into AI architectures.
• Build and Deploy AI Capabilities: Collaborate to deploy production-ready AI solutions.
• Optimise AI Performance: Improve answer quality, retrieval accuracy, latency, reliability and costs.
• Implement AI Evaluations: Create tests and monitoring for AI quality and failures.
• Ensure AI Reliability and Security: Implement guardrails, access controls, privacy protections and reliable execution.

Skills

Python

Asynchronous services

AI agents

RAG - Retrieval Augmented Generation

Embeddings

Retrieval

Reranking

Source grounding

Tools

AWS Bedrock

AgentCore Runtime

Strands Agents

OpenAI Codex

Claude Code

Job description

As our AI Engineer, you will take ownership of the AI layer of our product, ensuring the quality, reliability, performance, and continuous improvement of its AI capabilities.

You will be involved throughout the development lifecycle, from defining technical solutions and designing architectures to implementing, evaluating, deploying, and optimising AI systems.

We are looking for someone who can work independently, make sound technical decisions, and deliver production-ready AI solutions with minimal supervision.

Key Responsibilities

Design and Develop AI Solutions: Translate business requirements into practical AI architectures, determining when to use conventional software, retrieval systems, or AI agents.

Build and Deploy AI Capabilities: Collaborate with product and engineering teams to develop, test, deploy, and maintain production-ready AI solutions.

Optimise AI Performance: Improve answer quality, retrieval accuracy, response latency, reliability, and operational costs.

Implement AI Evaluations: Establish testing frameworks, performance metrics, and monitoring systems to measure AI quality and identify potential failures.

Ensure AI Reliability and Security: Implement appropriate guardrails, access controls, privacy protections, and reliable execution processes.

Continuously Improve Systems: Analyse production issues, identify root causes, and implement improvements to AI architecture and operating practices.

Required Technical Skills and Experience

We are looking for candidates with strong practical experience in the following areas:

1. AI Engineering and Architecture

Strong proficiency in Python and asynchronous services.

Experience developing AI agents, workflows, tool calling, MCP, structured outputs, state, and memory.

Solid understanding of Retrieval-Augmented Generation (RAG), embeddings, retrieval, reranking, and source grounding.

2. AWS AI Technologies

Hands-on experience with Amazon Bedrock and AgentCore.

Familiarity with AgentCore Runtime, Gateway, Memory, Identity, and Observability.

Experience with Strands Agents or comparable AI orchestration frameworks.

3. AI Evaluation and Monitoring

Experience developing evaluation datasets, regression tests, and adversarial tests.

Understanding of task-success metrics, retrieval performance, and AI response quality.

Ability to monitor production behaviour, analyse system traces, and identify performance issues.

4. AI Security and Reliability

Knowledge of prompt-injection prevention, access controls, tenant isolation, and data privacy.

Experience implementing retries, fallbacks, idempotency, and controlled tool execution.

Understanding of model versioning, prompt versioning, and quality-based release processes.

5. AI-Assisted Development

Strong practical experience using Claude Code and OpenAI Codex.

Ability to manage AI coding agents through clear instructions, context management, and scoped tasks.

Capable of reviewing, testing, and validating AI-generated code.

Additional Advantage:

Experience working with local or open-weight AI models, model serving, quantisation, hardware constraints, and self-hosted inference.