Associate Project Manager - Generative AI Data Operations
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 2d ago
The date the source published, not the day we noticed it (2026-09-30). Last seen at its source 1h ago.
We have tracked this listing since 30 Sep 2026 (1 days). The employer's own board has carried it every time we have read it, most recently 1 hour ago.
Is it remote?
The listing says yes
The location field doesn't say remote, so our assessment is based on the title or the description. Read the listing before applying.
Who may apply?
Asia
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay A$1,650–2,250/mo
Middle 50% of 17 listings that do state pay — Operations · all levels · Asia · AUD/month. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
workday employer's own board first seen 1d ago · last seen 1h ago
- location not stated
The listing
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Job Responsibilities:
Oversees multi-project portfolios for AI training data programs. Leads delivery and scale: capacity planning, vendor management, and process automation. Ensures quality is consistent across projects, drives performance improvements, and plans work jointly with the Sr. Quality Analyst. Oversees a portfolio of programs that deliver and scale Generative AI data operations, including capacity planning, vendor management, and process automation.”Key Responsibilities
Portfolio delivery: Plan and run a group of projects (collection, labeling, evaluation) end-to-end; set priorities, milestones, and handoffs across time zones.
Governance & reporting: Run cadence (status, risk, exec updates); align scope and budget with account and operations leads.
Capacity planning: Forecast and secure rater/annotator capacity; balance shifts, throughput, and skills across vendors and internal teams.
Quality consistency: Partner with the Sr. Quality Analyst on acceptance criteria, audits, and corrective actions; keep guidelines aligned across projects.
Process automation & tooling: Identify manual steps; pilot automation with Ops Tech (templates, scripts, RPA, API-driven flows); scale what works.
Vendor management: Set expectations, SLAs, and playbooks; review performance and drive improvements or changes as needed.
Financial control: Build and track budgets, burn, and margins; manage change orders to protect financial outcomes.
Risk, issue & change: Lead root-cause and action plans; escalate high-impact items with options and impact.
Client and stakeholder management: Lead planning and QBR-style reviews; explain results, risks, and next steps in clear terms.
Team enablement: Coach P1 PMs and C2–C3 Coordinators on planning, QA, and tools; support onboarding and skills growth (no formal line management required).
Compliance & security: Ensure data handling, privacy, and access controls are followed across all workstreams.
People Management: Gather feedback, provide training and coaching, foster team cohesion through team-building activities, conduct performance reviews, and support staffing and retention efforts. Additionally, collaborate with PST, Finance and recruiters for onboarding, offboarding, and addressing employee needs, while maintaining clear communication and updated SOPs to guide team.
Collaboration with Recruitment: Work closely with the recruiting team to manage hiring efforts by communicating requirements (e.g., language needs), upcoming projects, and candidate statuses. Review, evaluate, and select qualified candidates from recruiters and decide on next steps (e.g., assessments, interviews, or client presentation).
Additional Job Details:
Education
Bachelor’s degree or equivalent experience in business, operations, data/engineering, or similar
Experience
2–3 years leading multi-project portfolios or large multi-workstream programs in AI data, content review, labeling/annotation, or related fields
Background in capacity planning, vendor coordination, and quality systems; experience piloting or scaling process automation is a plus
Skills
Portfolio planning and governance across several projects at once
Clear communication with senior clients and internal leaders; runs planning and QBR-style reviews
Strong use of spreadsheets, PM/task boards, and basic BI; familiarity with SQL/ETL concepts is a plus
Sound judgment on scope, time, cost, and quality trade-offs
Negotiation and escalation to resolve risks, issues, and change
Coaching mindset; guides P1 PMs and C2–C3 Coordinators
Comfortable working with global, distributed teams (intermediate to advanced English)
Additional Qualifications (P1+)
Near-native English with strong writing and editorial skills
Hands-on experience with generative AI tools (text, voice, or video)
Background in QA testing, rubric design, or AI safety/ethics evaluation
Familiarity with data-annotation platforms and model-evaluation tools
Ability to interpret code, datasets, and system workflows at a conceptual level (no coding required)
Able to work independently and manage workflows effectively in a remote environment
Multilingual ability beyond English
Scope & Autonomy (P3 Alignment)
Owns outcomes for a portfolio of small/medium projects or a large multi-workstream program
Works independently; defines delivery approach and engages leaders for non-standard items
Joint planning and shared responsibility for quality and client outcomes with the Sr. Quality Analyst