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Salary
$176k – $312k per year (Estimated)
Location
Remote (United States)
Seniority
Architect · 8+ years exp
Employment
Full-Time
Overview
Company
Impact
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About Us ShareThis has unlocked the power of global digital behavior by synthesizing social share, interest, and intent data since 2007. Powered by consumer behavior on over three million global domains, ShareThis observes real‑time actions from real people on real digital destinations.

The Director of Product, Solution Implementation is an elite, individual contributor operating at the intersection of data product strategy, technical consulting, and enterprise architecture.

Serving as a trusted advisor to our highest-value enterprise accounts, you will own the end-to-end data strategy-from pre-sales solutioning through post-sales activation. In this role, you will act as a critical bridge: enabling sales to scope large deals, driving rapid time-to-value to secure long-term client retention, and spearheading next-generation data product prototyping to directly inform the product roadmap.

Responsibilities:

Strategic Solution Architecture & Sales Engineering

  • Partner with Enterprise Account Executives as the technical authority on high-value opportunities and licensing solutions for global brands, agencies and ecosystem partners.
  • Conduct deep-dive technical discovery sessions with client Engineers and Data Science teams to map a client’s business needs to Predactiv’s technical capabilities.
  • Design and present robust solution architectures, integration blueprints, and data-flow diagrams for prospective clients.

Implementation Governance

  • Serve as the technical leader for strategic deployments, establishing the engineering processes, validation checklists, and architectural standards that internal teams and third-party integrators must execute against.
  • Act as the premier technical escalation point for integration blockers, treating every issue as a data point to refine our standard deployment process.
  • Engineer repeatable frameworks for introducing early-stage product features, alphas, and betas to strategic clients, ensuring structured feedback loops that drive successful product rollouts.

Next-Gen Product Innovation

  • Partner with Product and Engineering to build early-stage data models and pipeline prototypes, using alpha/beta feedback to refine requirements.
  • Balance custom client demands with core solution scale, choosing repeatable, creative configurations over bespoke, tech-debt-heavy features.
  • Translate complex field challenges into structured technical requirements to ensure engineering builds scalable, platform-wide solutions.

Requirements:

  • Experience: 8+ years in a client-facing technical role (e.g., Principal Solutions Architect, Principal Sales Engineer, Data Scientist or Technical Account Manager).
  • AdTech & Ecosystem Mastery: Expert understanding of programmatic infrastructure (DSPs/SSPs), data clean rooms, identity resolution frameworks, and performance media metrics (e.g., lift, match rates, ROAS).
  • Data Architecture & Engineering: Strong proficiency in SQL, data modeling, big data environments, and complex integrations and real-time streaming feeds. Ability to read production code and write custom scripts to validate technical PoCs.
  • Agentic AI & Claude Proficiency: Hands-on experience deploying autonomous, multi-step AI agents and workflows utilizing Anthropic’s Claude ecosystem. Advanced prompt engineering and scripting skills used specifically to automate data validation and accelerate product prototyping.
  • Process Engineering: Proven capability to diagnose recurring, manual technical interventions and codify them into repeatable system workflows.

For compensation, we set standard ranges based roles based on function, level, and geographic location, benchmarked against similar stage growth companies. In order to be compliant with local legislation, as well as to provide greater transparency to candidates, we share salary ranges on all job postings regardless of desired hiring location. Final offer amounts are determined by multiple factors, including geographic location as well as candidate experience and expertise, and may vary from the amounts listed above.

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