About The Role
We’re looking for an
Associate Product Manager (APM)
to help drive our upcoming
AI product
from concept to scale. You’ll partner closely with design, data science/ML, engineering, GTM, and compliance to define requirements, measure outcomes, and ship features that customers love. This is a hands-on role for a structured thinker who’s comfortable with data, curious about LLMs and ML systems, and motivated to own outcomes—not just output.
What You’ll Do
Product Discovery & Strategy
- Map customer jobs-to-be-done, pain points, and current workflows for our target segments; maintain lean PRDs, problem statements, and success criteria.
- Translate ambiguous AI opportunities (e.g., “improve accuracy,” “reduce hallucinations”) into concrete hypotheses, experiments, and product bets.
- Contribute to product roadmap, balancing customer impact, technical feasibility, and risk (privacy, fairness, security, compliance).
Execution & Delivery
- Write crisp specifications: user stories, acceptance criteria, data contracts, and metrics definitions.
- Partner with DS/ML to define model evaluation frameworks (offline & online), human-in-the-loop review needs, and telemetry requirements.
- Coordinate sprint planning, backlog grooming, and release planning with engineering and design.
- Run betas and early-access programs; collect structured feedback and drive issue triage to resolution.
AI/ML Productization
- Define and track ground-truth datasets, labelling guidelines, and evaluation sets; ensure coverage across edge cases.
- Collaborate on prompt design, RAG pipelines, guardrails, and fallback strategies (e.g., confidence thresholds, deterministic backups).
- Partner with platform/security on PII handling, privacy-by-design, model safety, bias checks, and audit-ability.
- Establish A/B tests and online metrics (quality, latency, cost per call, safety triggers) and own the weekly review.
Go-To-Market & Customer Adoption
- Build enablement with PMM: positioning, messaging, demos, FAQs, release notes, and ROI calculators.
- Create “how to integrate” guides and work closely with Solutions/Support to unblock developers during pilots.
- Define pricing/packaging levers with business teams (usage/seat/feature gates) and monitor unit economics (GPU/token costs).
APM Key Responsibilities
- Own parts of the AI product surface (e.g., ingestion > enrichment > reasoning > delivery) and drive OKRs for quality, reliability, and adoption.
- Maintain a living metrics tree from product goals down to model-level KPIs (e.g., answer quality, coverage, latency, cost per 1K tokens, guardrail trigger rate).
- Specify observability needs: logs, traces, prompts, model versions, dataset lineage; ensure versioning and rollback plans exist.
- Define Data & Evaluation Contracts with DS/ML: input schemas, edge-case definitions, test sets, and “fail-safe” behavior.
- Partner with Design on UX patterns specific to AI uncertainty (confidence indicators, user control, clarifying questions).
- Document and socialize risk assessments (PII exposure, fairness/bias checks, jailbreak resistance) with Security/Legal.
- Drive customer discovery: 5–8 conversations per month; synthesize insights into roadmap decisions.
- Support PMM with launch planning, pricing experiments, and narrative storytelling.
What You’ll Bring (Minimum Qualifications)
- 2–3 years of experience in product management or adjacent roles (founder, solutions, data/business analyst, program management) shipping software.
- Demonstrated experience building data-rich or API-first products, developer platforms, or analytics/automation tools.
- Comfort working with data and metrics: writing clear success metrics, using dashboards (e.g., Mixpanel/Amplitude/Looker), and making trade-offs based on evidence.
- Working understanding of LLMs/ML concepts: datasets, prompts, embeddings, RAG, evaluation metrics (precision/recall, BLEU/ROUGE, BERTScore, hallucination rate), and cost/latency trade-offs.
- Strong execution skills: turning vague requirements into prioritized backlogs, writing high-signal PRDs, driving cross-functional alignment.
- Excellent communication with customers and internal stakeholders.
Nice-to-Have
- Hands-on experience with any of: Python/SQL, experiment platforms, feature stores, vector databases, observability for ML, or model safety/guardrails.
- Experience in privacy, security, or regulated environments.
- Exposure to B2B SaaS and developer-facing products.
- Understanding of the creator/data ecosystem, workflows, and integrations (APIs, webhooks, OAuth).
Skills & Competencies
- Customer-obsessed: Starts with the problem, not the solution.
- Systems thinker: Can reason through data pipelines, model constraints, and product UX.
- Analytical: Uses data to decide, not decorate; comfortable with SQL/basic Python a plus.
- Clear communicator: Writes precise PRDs, speaks the language of engineers, designers, and customers.
- Bias to action: Pragmatic about shipping incremental value while paying down tech and data debt.
- Ethical & privacy-minded: Designs with user consent, transparency, and safety in mind.
What We Offer
Work from home:
Work from home or your preferred location.
Flexible hours:
Choose to work in the hours you feel the most productive.
Innovate and Evolve:
We’re building a high-growth, high-autonomy culture. We rely less on job titles and more on cultivating an environment where anyone can contribute, the best ideas win, and personal growth is driven by expanding impact and less by title.
