Associate Director of Product Management at Blend360

Columbia, Maryland, United States -

Full Time

Start Date

Immediate

Expiry Date

19 Jan, 26

Salary

0.0

Posted On

21 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Product Management, Agile Methods, Data Analysis, Communication, Problem Solving, Collaboration, Analytics, User Experience, AI Features, Experimentation, Technical Concepts, Backlog Management, Customer Interviews, KPI Definition, Risk Management, Process Engineering, B2B2C Products

Industry

Professional Services

Description

Company Description Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. Our company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com. Qualifications About the Role We’re looking for an Associate Director of Product Management to own outcomes from problem discovery through delivery and iteration. You’ll partner with design, engineering, data, and ops to build internal agentic based products. What You’ll Do Write crisp specs: articulate requirements, acceptance criteria, and success metrics; ensure shared understanding across teams especially detail required for engineers developing agentic solutions so the focus on process and workflow and intended outcome is key. Complete these tasks with urgency. Drive discovery: run customer interviews, analyze data, map jobs-to-be-done, and validate problem-solution fit. Prioritize ruthlessly: create and maintain a clear backlog; use impact/effort, ROI, and risk to make trade-offs. Ship iteratively: lead agile rituals, remove blockers, and deliver high-quality increments on predictable cadences. Communicate clearly: craft narratives, demos, and updates for executives and stakeholders. Measure outcomes: instrument analytics, define KPIs/OKRs, and run experiments to improve activation, retention, and revenue. Partner cross-functionally: collaborate with design on UX, with engineering on architecture & feasibility, and with GTM on launches. Understand the product area: read the vision, strategy, and roadmap aligned to company goals and customer needs, ask questions and ingrain yourself of what its intended to do. When AI/Agentic is In-Scope Define data and model requirements, evaluation criteria, and guardrails for AI features. Partner with ML/AI engineers on experimentation, offline/online evals, and human-in-the-loop workflows. Balance accuracy, latency, cost, and safety; manage model/version lifecycle and tests. Additional Information 3–7+ years in product management (or equivalent founder/PMM/consulting/eng background). Very familiar with technical concepts and trade-offs; you can go deep without losing the big picture. Proven track record shipping products end-to-end under tight timelines. Strong product sense, structured problem solving, and analytical rigor. Excellent written and verbal communication; ability to align diverse stakeholders. Experience with agile methods and experimentation (feature flags, A/B testing). Nice to Have: Exposure to LLMs/ML systems, retrieval/RAG, evaluation frameworks, prompts/guardrails, and data pipelines. Understanding of privacy, security, compliance, and model risk management. Familiarity with metrics like hallucination rate, task success rate, latency, and cost per action. Domain experience in process engineering, bpo, and managed services. Experience in B2B2C or platform/ecosystem products. Background in design, engineering, data, or operations.

Responsibilities

The Associate Director of Product Management will own outcomes from problem discovery through delivery and iteration, partnering with various teams to build internal agentic-based products. Key tasks include writing specifications, driving discovery, prioritizing tasks, and measuring outcomes.