AI Architect

Job Description:

The AI Language Architect combines traditional translation and review skills with a strategic approach focused on optimizing LLM-based localization outputs. This position bridges the gap between human linguistic expertise and AI capabilities to drive linguistic accuracy, system autonomy, and operational efficiency across markets.

Key Responsibilities:

1. Prompt Engineering & System Optimization

• Refine system prompts to improve LLM output accuracy, tone, and style.

• Identify recurring error patterns and translate them into actionable instructions for the LLM.

• Manage the feedback loop between LLM output and desired target language standards.

2. Error Root Cause Analysis (ERCA)

• Perform a deep-dive analysis on rejected translations to distinguish between "linguistic preference" and "systemic LLM hallucination."

• Categorize errors by source (e.g., glossary gaps, ambiguity, cultural misalignment) to guide iterative model improvements.
  

3. Quality Metrics & Auditing

• Implement and track key performance indicators (KPIs) such as percentage of words changed (Human Edit Distance, HED), Error Density, and Multidimensional Quality Metrics (MQM) scores.

• Drive the transition from 100% manual review to exception-based auditing, focusing on high-risk and high-visibility content.

• Conduct quarterly quality health checks to ensure the system maintains parity as it gains autonomy.

4. Data Curation & Asset Management

• Maintain and evolve localized glossaries, style guides, and gold standard datasets to serve as training inputs for the LLM.

• Collaborate with the localization lead and Cisco’s regional teams to ensure terminology consistency and brand voice.

Required Competencies

• Linguistic Expertise: Native-level fluency in French, with high proficiency in English.

• Analytical Mindset: Ability to identify systemic patterns rather than focusing solely on individual string corrections.

• Prompt Engineering Awareness: Interest in or experience with LLM prompting techniques and data annotation.

• Strategic Thinking: Ability to balance immediate quality needs with long-term goals of system automation.

• Adaptability: Experience or interest in evolving from a translator role to a system architect role within a fast-paced technical environment.

Success Metrics (KPIs)

• HED Reduction: Steady decrease in Human Edit Distance for standard content.

• Error Density: Maintaining critical error rates at near-zero levels.

• Automation Velocity: Successfully migrating content categories from human-review to automated-audit workflows.

• System Stability: Ensuring consistent terminology and style application across localized sites.