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Talkiatry · 1 day ago

Senior Manager, AI Strategy & Operations

New York, NY

Full-time

Onsite

Senior Level

$135K/yr - $165K/yr

7+ years exp

Talkiatry is a company focused on reimagining patient care through AI technology. The Senior Manager, AI Strategy & Operations will lead the design and deployment of AI solutions to enhance patient interactions and operational efficiency while collaborating with cross-functional teams to integrate AI across the organization.

Health CareMedicalMental HealthmHealthWellness

Responsibilities

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

Qualification

AI StrategyProduct ManagementConversational AIProject ManagementVendor ManagementData AnalyticsTechnical SpecificationEthical AI PracticesCommunication Skills

Required

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