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Ai Strategy Director Jobs in Reno, NV (NOW HIRING)

... strategic readiness. This is a highly visible, mission critical leadership position reporting to ... Leverage SPA to drive automation and process improvements including AI tool sets. Ensure timely and ...

Director Accounting Operations

Sparks, NV · On-site

$180 - $230/hr

... strategic readiness. This is a highly visible, mission critical leadership position reporting to ... Leverage SPA to drive automation and process improvements including AI tool sets. * Ensure timely ...

... strategic readiness. This is a highly visible, mission critical leadership position reporting to ... Leverage SPA to drive automation and process improvements including AI tool sets. Ensure timely and ...

Hospice Executive Director

Reno, NV · On-site

$140 - $180/hr

Nestmed AI Scribe : Less charting, more caring! * Competitive pay, 401k, health & life insurance ... Supports the Account Executive and VP of Strategic Initiatives in the community to ensure the ...

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Ai Strategy Director information

See Reno, NV salary details

$101.7K

$138.7K

$242.3K

How much do ai strategy director jobs pay per year?

As of Aug 29, 2026, the average yearly pay for ai strategy director in Reno, NV is $138,693.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,200.00 and $144,600.00 per year, depending on experience, location, and employer.

What does an AI Strategy Director do?

An AI Strategy Director is responsible for developing and overseeing an organization's approach to implementing artificial intelligence technologies. They align AI initiatives with business goals, manage cross-functional teams, and ensure projects deliver measurable value. This role involves identifying opportunities for AI adoption, guiding ethical use, and staying updated on industry trends. The AI Strategy Director often collaborates with executives, data scientists, and IT professionals to drive innovation and competitive advantage.

What are the key skills and qualifications needed to thrive as an AI Strategy Director?

To thrive as an AI Strategy Director, you need deep expertise in artificial intelligence, business strategy, data analytics, and a relevant advanced degree such as an MBA or MSc in a technical field. Familiarity with AI development tools, data platforms, and project management systems, along with certifications like PMP or in AI/ML, is highly valuable. Exceptional leadership, strategic thinking, and communication skills help drive cross-functional alignment and inspire innovation. These abilities are critical for designing and executing successful AI initiatives that deliver business value and maintain a competitive edge.

How does an AI Strategy Director typically collaborate with cross-functional teams to implement AI initiatives?

An AI Strategy Director works closely with cross-functional teams, including data scientists, engineers, business leaders, and product managers, to identify opportunities for AI integration and drive successful project execution. They facilitate communication between technical and non-technical stakeholders, ensuring that AI solutions align with business objectives and regulatory requirements. Regular meetings, workshops, and progress reviews are common, enabling the AI Strategy Director to guide teams through challenges, monitor project milestones, and adjust strategies as needed. This collaborative approach is essential for bridging the gap between innovative AI technologies and real-world business impact.

What is the difference between Ai Strategy Director vs Data Scientist?

AspectAi Strategy DirectorData Scientist
Required CredentialsAdvanced degrees in AI, Data Science, or related fields; leadership experienceBachelor's or Master's in Data Science, Computer Science, or related fields
Work EnvironmentStrategic planning, cross-department collaboration, executive meetingsData analysis, model development, coding, and experimentation
Employer & Industry UsageTech companies, AI-focused firms, large enterprisesTech companies, research institutions, startups
Search & Comparison IntentUnderstanding leadership roles in AI strategyTechnical data analysis and modeling roles

The Ai Strategy Director focuses on high-level AI strategy, leadership, and aligning AI initiatives with business goals. In contrast, Data Scientists are hands-on technical experts who develop models and analyze data. Both roles are vital in AI-driven organizations but differ in scope, responsibilities, and required experience.

What job categories do people searching Ai Strategy Director jobs in Reno, NV look for?

The top searched job categories for Ai Strategy Director jobs in Reno, NV are:

What cities near Reno, NV are hiring for Ai Strategy Director jobs?

Cities near Reno, NV with the most Ai Strategy Director job openings:

Infographic showing various Ai Strategy Director job openings in Reno, NV as of August 2026, with employment types broken down into 74% Full Time, 22% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $138,693 per year, or $66.7 per hour.

Cloud Solutions Architect / Database Engineer / AI Platform Architect

ABCO MAINTENANCE INC. (BIC# 1854)

Reno, NV

$150K - $180K/yr

Full-time

Posted 22 days ago


Job description

We are seeking a highly experienced Cloud Solutions Architect / Database Engineer / AI Platform Architect to design and build the cloud, database, security, API, and AI infrastructure that supports our enterprise applications. Compensation for thisrole will bebetween $150k-$180k depending on experience. This role will be responsible for establishing scalable cloud architecture, designing and engineering production databases, developing secure APIs and integration services, implementing authentication and application security standards, and architecting the AI foundation of our applications.

The architect will build the backend and AI service layers that allow front-end developers to securely and efficiently consume application data, business functionality, and AI-powered capabilities.The ideal candidate will have deep expertise in cloud architecture, C#/.NET, SQL Server, database engineering, REST APIs, application security, authentication, Azure or AWS, enterprise integrations, and production AI architecture . This individual should be capable of taking business and application requirements and translating them into secure, scalable, production-ready technical solutions. Experience with AI and Large Language Model (LLM) platforms is required, particularly when designing the infrastructure, data access, security, APIs, and application architecture necessary to support AI-powered enterprise solutions

The ideal candidate will have hands-on experience building production AI applications using OpenAI, Azure OpenAI, Anthropic, Google AI, or comparable LLM technologies, including designing workflows that enable AI to execute complex business processes through structured instructions, examples, retrieval strategies, orchestration, and enterprise data integration. This role requires experience developing AI as an operational component of an application, not simply integrating an AI API or adding chatbot functionality. Responsibilities Architect and implement scalable, secure, and highly available cloud environments for enterprise applications.

Design the overall backend architecture supporting web applications, internal systems, integrations, and AI-powered solutions. Design, build, and maintain production database environments, including schemas, tables, relationships, stored procedures, views, indexing strategies, and data-access patterns. Develop and optimize SQL Server databases for performance, scalability, reliability, data integrity, and security.

Establish database standards covering data modeling, normalization, indexing, query optimization, auditing, backup, recovery, and disaster recovery. Design and develop secureRESTful APIs and backend services using C#, ASP.NET Core, and related .NET technologies. Build well-structured API and service layers that allow front-end developers to consume data and business functionality without requiring direct access to backend systems or databases

Define API contracts, request/response models, validation standards, error handling, versioning, documentation, and integration patterns. Implement authentication and authorization solutions using technologies and standards such asOAuth 2.0, OpenID Connect, JWT, SSO, RBAC, and enterprise identity providers. Design and enforce application and API security standards, including SSL/TLS, encryption, secrets management, certificate management, secure configuration, and least-privilege access

Implement secure communication between cloud services, databases, APIs, external systems, AI services, and front-end applications. Design cloud networking and infrastructure components including application hosting, databases, storage, identity, networking, firewalls, gateways, load balancing, monitoring, logging, and availability strategies. Develop integration architectures for internal systems, third-party applications, vendor APIs, and enterprise platforms.

Design data pipelines, ETL processes, data transformation services, and system-to-system integrations where required. Establish logging, monitoring, auditing, alerting, and observability standards across backend services and cloud infrastructure. Design scalable architectures capable of supporting increasing users, transaction volumes, data volumes, integrations, AI workloads, and application workloads.

Implement caching, asynchronous processing, queues, background services, and other distributed architecture patterns when appropriate. Develop and maintain CI/CD pipelines and infrastructure deployment processes. Work closely with front-end developers to define API requirements, data contracts, authentication flows, AI service interactions, and integration standards.

Design and implement AI workflow architectures that enable Large Language Models to perform complex business functions by defining process sequences, system instructions, prompt strategies, retrieval mechanisms, examples, evaluation methods, tool interactions, and orchestration workflows. Architect AI systems capable of incorporating enterprise knowledge and business processes through structured process definitions, contextual examples, retrieval, tool use, and iterative refinement so that AI can reliably execute operational business tasks. Design Retrieval-Augmented Generation (RAG) architectures that securely retrieve relevant enterprise information from databases, documents, APIs, vector stores, and other approved business data sources.

Design secure AI integration patterns that control how LLMs access enterprise databases, APIs, internal systems, and sensitive business information. Establish AI evaluation, testing, monitoring, and quality standards to measure accuracy, reliability, consistency, security, and effectiveness of AI-powered workflows. Collaborate with business stakeholders and development teams to translate application requirements and business processes into technical and AI architectures.

Evaluate technical risks, scalability requirements, security concerns, infrastructure costs, AI usage costs, and architectural tradeoffs. Conduct architecture and code reviews and establish backend, database, API, cloud, security, and AI development standards. Provide technical leadership and mentoring to developers working within the architecture.