Context Manager

Job Overview

This role involves transforming high-level industry challenges and specific business demands into actionable data science, prompt engineering, and large language model (LLM) focused requirements. The candidate will prioritize AI feature development by balancing algorithmic difficulty, data access, and anticipated business outcomes to enhance AI return on investment.

Key Responsibilities

• Convert complex business problems and domain-specific needs into concrete AI and LLM engineering specifications.
• Optimize AI product backlogs to maximize business value, considering algorithmic complexity and data availability.
• Define and manage requirements tailored for machine learning and cognitive systems, including writing synthetic user stories, acceptance criteria, and handling probabilistic outcomes.
• Revamp existing process flows by incorporating agentic workflows and automated decision-making, including designing human-in-the-loop feedback systems for continuous model improvement.
• Establish governance frameworks and service level agreements (SLAs) that address non-deterministic AI outputs, including defining thresholds for accuracy, latency, and hallucinations, while ensuring compliance with organizational ESG and responsible AI standards.

Core Skills

• Expertise in generative AI and large language models, including knowledge of their capabilities, limitations, architectures, token economies, and cost optimization techniques.
• Strategic understanding of agentic system architectures, capable of distinguishing between deploying point solutions versus autonomous multi-agent systems.
• Proficiency in prompt engineering and model guidance, including refining system prompts, guardrails, and semantic structures to align with brand requirements.

Experience

The role requires extensive work experience ranging from 7 to 10 years in relevant AI and data science fields.