AI Harness Engineer

Horizontal Talent; Kuala Lumpur; On-site; MYR 180,000 - 260,000; Full time

Job summary

Horizontal Talent is seeking a senior AI/ML engineering professional to lead and advance our AI development workflows in a fast-paced environment. You will monitor frontier models, evaluate vendors, and shape practical AI strategies with a focus on security, governance, and efficiency.

Responsibilities include building internal evaluation benchmarks, defining robust prompt and context engineering standards, and implementing scalable tooling to empower engineering teams across the organization.

Qualifications

• Extensive hands-on experience with agentic coding tools such as Claude Code, Codex, Cursor.
• Strong understanding of prompt engineering, context engineering, and model evaluation methodologies.

Responsibilities

• Continuously monitor and evaluate leading AI vendors, frontier models, and emerging AI technologies, assessing their capabilities, cost, context handling, and agentic performance.
• Develop and implement a vendor diversification and resilience strategy by evaluating alternative AI vendors, model routing solutions, and self-hosted LLM options.
• Build and maintain internal AI evaluation benchmarks based on real-world codebases and business scenarios to objectively measure and compare model performance.
• Take ownership of and continuously improve company-wide AI development workflows and best practices, including prompt and context engineering standards, agent configurations, code review and validation processes, and safety guardrails.
• Define and enforce AI security and compliance standards to prevent source code and sensitive data leakage, mitigate prompt injection risks, establish security review requirements for AI-generated code, and implement appropriate data masking and access controls.
• Build and maintain internal AI harnesses and developer tooling, including shared configurations, skills and plugins, evaluation scripts, and CI integrations, enabling engineering teams to adopt AI tools efficiently.
• Document AI development best practices, conduct technical training and knowledge-sharing sessions, and track AI adoption and developer productivity metrics across engineering teams.

Skills

Prompt engineering

Model evaluation

Cross-functional collaboration

Tools

Claude Code

Codex

Cursor

Job description

About Horizontal: Established since 2003 in the US, Horizontal solves complex challenges across two distinct businesses: Horizontal Digital and Horizontal Talent. We are consistently recognized for being a top workplace and one of the fastest growing private companies. Horizontal Talent specializes in staffing for IT, Digital & Creative and Business & Strategy markets. We have global offices in US, UAE, India, Malaysia and Australia.

Job Responsibilities

• Continuously monitor and evaluate leading AI vendors, frontier models, and emerging AI technologies, assessing their capabilities, cost, context handling, and agentic performance. Provide clear recommendations on model suitability and adoption.
• Develop and implement a vendor diversification and resilience strategy by evaluating alternative AI vendors, model routing solutions, and self-hosted LLM options. Establish reliable fallback and switching mechanisms to reduce dependency on a single vendor.
• Build and maintain internal AI evaluation benchmarks based on real-world codebases and business scenarios to objectively measure and compare model performance.
• Take ownership of and continuously improve company-wide AI development workflows and best practices, including prompt and context engineering standards, agent configurations, code review and validation processes, and safety guardrails.
• Define and enforce AI security and compliance standards to prevent source code and sensitive data leakage, mitigate prompt injection risks, establish security review requirements for AI-generated code, and implement appropriate data masking and access controls.
• Build and maintain internal AI harnesses and developer tooling, including shared configurations, skills and plugins, evaluation scripts, and CI integrations, enabling engineering teams to adopt AI tools efficiently.
• Document AI development best practices, conduct technical training and knowledge-sharing sessions, and track AI adoption and developer productivity metrics across engineering teams.

Requirements

• Extensive hands-on experience with agentic coding tools such as Claude Code, Codex, Cursor, or similar tools, with practical knowledge of the strengths and limitations of different frontier AI models.
• Strong understanding of prompt engineering, context engineering, and model evaluation methodologies, including benchmark design and evaluation harnesses.
• Strong technical curiosity and self-motivation, with the ability to independently follow developments in the rapidly evolving AI ecosystem, conduct evaluations, and translate findings into actionable recommendations.
• Good understanding of key LLM and AI application security risks, including data leakage, prompt injection, and supply chain risks associated with AI-generated code, as well as relevant mitigation practices.
• Excellent written communication and cross-functional collaboration skills, with the ability to establish and drive engineering standards across multiple teams.
• Experience in LLM application development, AI evaluation frameworks, developer productivity, or platform engineering.
• Experience with self-hosted LLM deployment, model routing, or AI inference infrastructure.
• Open-source contributions, technical blogging, public speaking, or other forms of technical knowledge sharing.