Job Description

The Mission

As the Manager, Solutions & Delivery , being the critical bridge between our clients and our global delivery teams. Your role is to translate abstract research goals (e.g., Make the model wittier ) into concrete, executable engineering standards (SOPs), ensuring we deliver the Golden Standard of data every time.

Key Responsibilities

1. Pre-Sales Solutioning & Technical Scoping

• Requirement Translation: Partner with the Account manager during early client engagements to analyze complex technical requirements. Translate vague requests (e.g., Improve safety boundaries) into specific data strategies (e.g., Adversarial Red Teaming protocols).
• Pilot Architecture: Lead the design and execution of Proof of Concept (POC) pilots. Define the initial prompt sets, grading rubrics, and success metrics to win client confidence.

2. Delivery Architecture & SOP Engineering

• Guideline Authoring: Write and maintain the Bible for each projectcomprehensive Style Guides and Standard Operating Procedures (SOPs). You must define what Good looks like for complex tasks such as Chain-of-Thought (CoT) reasoning or Persona-based Creative Writing .
• Workflow Integration: Collaborate with the R&D team to integrate new tools into the production workflow to improve efficiency.

3. Quality Assurance & Dual-Evaluation

• Client Alignment: Act as the primary technical point of contact during delivery. Lead weekly quality calibration calls with clients to defend our data decisions and align on edge cases.

4. Resource Orchestration

• Capacity Planning: Forecast talent needs based on the sales pipeline. Issue precise Talent Profiles to the Operations/Recruiting team (e.g., We need 20 native French speakers with coding backgrounds by next week ).
• Delivery Oversight: Monitor the overall health of multiple concurrent projects. Identify bottlenecks in throughput or quality and intervene with process adjustments before they impact the client.

Requirements

• Experience: 35+ years of experience in Technical Program Management, Solutions Engineering, or Delivery Management within the AI Data, Localization (LSP).
• Domain Knowledge: Familiarity with the LLM data lifecycle ( SFT, RLHF, DPO ). You understand the difference between a simple Q&A and a multi-turn reasoning task.
• Data Literacy: Comfortable using Excel/Sheets for data analysis; basic Python skills or SQL knowledge to query dataset progress is a strong plus.
• Communication: Fluency in English is non-negotiable. You must be confident presenting to PhD-level researchers and demanding product owners.

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