Talkiatry

Senior Manager, AI Strategy – Operations

Talkiatry

full-time

Posted on:

Location Type: Hybrid

Location: New York City • New York • 🇺🇸 United States

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Salary

💰 $135,000 - $165,000 per year

Job Level

Senior

Tech Stack

ServiceNow

About the role

  • Partner with Product and Engineering leadership to define Talkiatry’s long-term AI infrastructure strategy, ensuring interoperability across platforms (Genesys, ServiceNow, Talkiatry core platforms, Snowflake, LLMs).
  • Gather and translate patient needs and agent workflows into AI product requirements (voice and text), defining intents, escalation paths, and response hierarchies that balance safety, automation, and empathy.
  • Evaluate emerging technologies to guide the roadmap for AI tooling, model management, and automation pipelines.
  • Ensure every AI initiative advances Talkiatry’s goals of access to care, quality, and workforce efficiency.
  • Champion responsible AI principles in vendor selection, governance, and deployment practices.
  • Own day-to-day AI performance through platform dashboards, tracking metrics such as containment rate, CSAT, response accuracy, and resolution efficiency.
  • Conduct root-cause analyses on performance deviations, partnering with Product, Engineering, and Ops to translate results into model or workflow improvements.
  • Surface performance insights to the Quality & Training team for incorporation into AI retraining, QA frameworks, and knowledge base updates.
  • Maintain governance documentation for model versions, updates, and validation to ensure transparency and compliance.
  • Oversee the AI-facing knowledge infrastructure, including taxonomy design, content ingestion workflows, and integration of source-of-truth systems.
  • Define and maintain prompt engineering and response standards for AI agents and copilots.
  • Collaborate with the Quality & Training team, who owns content creation, article optimization, and training for human and AI learners.
  • Build structured feedback loops from frontline teams and Operations to refine prompts, content, and knowledge architecture.
  • Establish unified processes for testing, version control, and model retraining tied to knowledge updates.
  • Lead full-lifecycle AI implementations, from scoping and vendor selection to pilot, launch, performance tracking and optimization.
  • Manage AI vendor relationships, holding partners accountable to performance and timely delivery.
  • Develop clear project roadmaps, success metrics, and communication plans across Product, Engineering, and Operations.
  • Collaborate on documentation, training materials, and rollout support for internal and external stakeholders.

Requirements

  • 7+ years of experience in product management, process automation, or technology operations, with hands-on experience applying AI or large language model (LLM) solutions to real-world workflows.
  • Proven success delivering large-scale AI or automation projects from concept through deployment.
  • Strong understanding of conversational AI platforms and voice/text agent design principles, with the systems thinking to architect how AI connects across data, telephony, CRM, and workflow tools (e.g., APIs, integrations, enterprise systems).
  • Highly analytical with experience in product and operational analytics.
  • Skilled at translating business and user requirements into technical specification; experience in product management, technical program management, or systems enablement preferred.
  • Exceptional project management and vendor management capabilities; thrives in cross-functional environments.
  • Excellent communication skills – clear, structured, and equally fluent with technical and non-technical stakeholders.
  • Committed to ethical AI practices and data integrity in healthcare contexts.
Benefits
  • Excellent benefits: medical, dental, vision, effective day 1 of employment
  • 401K with match
  • Generous PTO plus paid holidays
  • Paid parental leave

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
AI infrastructure strategyAI product requirementsmodel managementautomation pipelinesperformance metricsroot-cause analysisprompt engineeringproject managementvendor managementlarge language model (LLM)
Soft skills
analytical skillscommunication skillscross-functional collaborationprocess optimizationstakeholder engagementproblem-solvingproject roadmap developmentfeedback loop creationteam leadershipethical AI commitment