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 project—comprehensive 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 : 3–5+ 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.