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Assistant Ai Strategy Jobs in Arizona (NOW HIRING)

Develops and implements operating plans for enhancing the business and meeting strategic objectives ... CNA utilizes AI-enabled technology during the recruiting process. For more information, please ...

Java Springboot AI Developer

Phoenix, AZ · On-site

$50.75 - $65.50/hr

... strategies, analyse results, and coordinate bug fixes to uphold the software quality standards • ... assist other similar projects Your contribution to the team: • A collaborative spirit and ...

As a senior consultant on the Business Strategy team, you will be responsible for: * Assist in ... AI transformation. Deloitte's Business Strategy team helps clients tackle their most critical ...

Product Owner- AI Platforms

Phoenix, AZ · Hybrid

$102K - $136K/yr

Translate strategy into actionable tasks, and work with cross-functional agile teams to ensure ... Develop UI prototypes, assist with data provisioning, and perform analytics around usage ...

Product Owner- AI Platforms

Phoenix, AZ · Hybrid

$102K - $136K/yr

Translate strategy into actionable tasks, and work with cross-functional agile teams to ensure ... Develop UI prototypes, assist with data provisioning, and perform analytics around usage ...

Define and implement the strategic vision for the team, balancing short-term goals with long-term ... Additionally, TSMC provides income-protection programs to financially assist you should you ...

... and strategic thinking. Fox is hiring a Senior Engineer, AI Site Reliability to help build and ... Help to mentor and train less senior members of the team * Assist with product/technology selection ...

Showing results 21-40

Assistant Ai Strategy information

What is an assistant AI strategy?

An Assistant AI Strategy refers to the planning and implementation of artificial intelligence technologies, such as digital assistants, to support and enhance business operations. This role involves analyzing current AI trends, identifying opportunities for AI integration, and recommending best practices for deploying AI assistants. The goal is to improve efficiency, automate routine tasks, and provide valuable insights for decision-making. Professionals in this field work closely with technical teams and business stakeholders to align AI initiatives with organizational objectives.

What are some typical challenges an assistant AI strategy professional might face when supporting the development and implementation of AI initiatives?

As an Assistant AI Strategy professional, you'll often encounter challenges such as aligning AI initiatives with overall business objectives, managing stakeholder expectations, and navigating evolving technologies. You may also need to balance the need for innovation with concerns about data privacy, ethical use, and regulatory compliance. Collaborating effectively across technical, business, and operations teams is crucial to ensure the successful integration of AI solutions within existing workflows.

What are the key skills and qualifications needed to thrive as an assistant AI strategist, and why are they important?

To thrive as an Assistant AI Strategist, you need a solid understanding of artificial intelligence concepts, data analysis, and strategic planning, often supported by a degree in computer science, data science, or business. Familiarity with tools like Python, machine learning platforms (such as TensorFlow or Azure ML), and data visualization software is commonly required. Strong communication, critical thinking, and collaborative skills help you effectively bridge technical teams and business stakeholders. These skills ensure successful AI project implementation and alignment with organizational goals.

What is the difference between Assistant Ai Strategy vs Data Analyst?

AspectAssistant Ai StrategyData Analyst
Required CredentialsBachelor's in Computer Science, AI, or related fields; familiarity with AI toolsBachelor's in Statistics, Data Science, or related fields; proficiency in data analysis tools
Work EnvironmentTech companies, AI startups, R&D teamsBusiness, finance, healthcare, and other industries
Employer & Industry UsagePrimarily in AI-focused roles within tech and innovation sectorsAcross various industries for data-driven decision making

The Assistant Ai Strategy role focuses on developing and implementing AI strategies, working closely with AI teams, and understanding AI technologies. In contrast, a Data Analyst primarily interprets data, creates reports, and supports business decisions through data insights. While both roles require analytical skills, Assistant Ai Strategy emphasizes AI knowledge and strategic planning, whereas Data Analysts focus on data manipulation and analysis.

How do I become an assistant AI strategist?

To become an assistant AI strategist, develop a strong foundation in artificial intelligence, machine learning, and data analysis through relevant degrees or certifications. Gaining experience with AI tools, programming languages like Python, and understanding business applications of AI can enhance your qualifications for this role.

What is the easiest assistant AI strategy job to get into?

Entry-level assistant AI strategy roles typically require a basic understanding of AI concepts, data analysis, and familiarity with tools like Python or machine learning frameworks. Candidates often start with internships or related positions in data analysis or AI support, and building a foundational knowledge through online courses or certifications can improve chances of entry.

What are the most commonly searched types of Ai Strategy jobs in Arizona?

The most popular types of Ai Strategy jobs in Arizona are:

What are popular job titles related to Assistant Ai Strategy jobs in Arizona?

For Assistant Ai Strategy jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Assistant Ai Strategy jobs in Arizona look for?

The top searched job categories for Assistant Ai Strategy jobs in Arizona are:

What cities in Arizona are hiring for Assistant Ai Strategy jobs?

Cities in Arizona with the most Assistant Ai Strategy job openings:

Senior Product Manager, AI

AccusourceHR Career Page

Phoenix, AZ • On-site

$110K - $140K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 25 days ago


Job description

Description:

Job Title: Senior Product Manager

Department: Product

Reports To: Chief Product Officer

Employment Type: Full-Time, Salary-Exempt, Remote

Salary: $110,000-$140,000


About AccuSourceHR: AccuSourceHR is a full-service employment screening organization headquartered in Phoenix, Arizona. Since 1999, we have helped employers make faster, safer, and more confident workforce decisions through reliable screening technology, high-quality client care, and PBSA-accredited practices.
We are investing in modern product experiences, integrations, automation, data-driven insights, and practical AI capabilities that help customers operate more efficiently and with greater confidence.


Position Overview

As a Senior Product Manager, you'll lead the end-to-end product life cycle, from ideation to launch and iteration. Collaborating with cross-functional teams, including engineering, UX/UI, operations, implementation, and marketing, you'll develop scalable, user-centric solutions that align with our mission to enhance workforce screening services. What you will own:


Product Strategy and Roadmap

  • Own product strategy and roadmap for AI-enabled capabilities, workflow automation, data-driven insights, integrations, and platform improvements.
  • Translate customer problems, business goals, technical possibilities, and operational constraints into clear product priorities.
  • Define MVPs, phased releases, success metrics, rollout plans, and risk controls.
  • Build business cases tied to revenue, retention, efficiency, risk reduction, or competitive differentiation.
  • Decide where AI creates durable value and where rules-based workflow or deterministic automation is the better answer.

AI Product Development

  • Partner with engineering to design, test, and launch AI-enabled features, copilots, assistants, agents, conversational experiences, and intelligent workflows.
  • Define user journeys, permissions, tool interactions, guardrails, fallback logic, escalation paths, confidence thresholds, and human review requirements.
  • Write clear requirements involving prompts, context engineering, structured outputs, retrieval, workflow orchestration, model limitations, evaluation criteria, and release readiness.
  • Design natural-language experiences that help users ask questions over complex data and receive structured, defensible answers such as summaries, tables, explanations, or recommended next steps.
  • Define release-readiness criteria for AI features, including hallucination handling, PII protection, audit trails, observability, rollback plans, and user transparency.
  • Use modern AI tools in your own PM workflow for research, synthesis, requirements, analysis, and prototyping.

Workflow and Domain Leadership

  • Develop deep understanding of customer workflows across screening, compliance operations, document management, monitoring, business-system integrations, and regulated operational environments.
  • Identify opportunities to connect fragmented workflows, data sources, partner systems, and customer operations into clearer product experiences.
  • Frame integration depth, data contracts, permissions, data quality, and build-versus-partner tradeoffs as product decisions.
  • Partner with customers and internal teams to understand real workflows, edge cases, compliance requirements, operational pain points, and buyer priorities.

Discovery and Execution

  • Conduct customer discovery, stakeholder interviews, workflow analysis, competitive research, and market assessment.
  • Shadow or interview users who operate complex workflows so product decisions are grounded in real operator behavior, not assumptions.
  • Use customer feedback, support trends, usage data, sales input, implementation friction, and market signals to inform priorities.
  • Track foundation model releases, agent frameworks, AI evaluation methods, and relevant workflow automation trends.
  • Define personas, jobs-to-be-done, user journeys, problem statements, product hypotheses, and adoption risks.
  • Lead cross-functional execution across engineering, UX, operations, implementation, compliance, customer success, sales, and marketing.

Responsible AI and Measurement

  • Partner with engineering, security, compliance, legal, and operations to manage risks related to sensitive data, PII, bias, explainability, auditability, and human oversight.
  • Define when AI should recommend, summarize, classify, draft, automate, escalate, or stay out of the workflow.
  • Establish product-level AI governance practices, including evaluation criteria, monitoring, documentation, user transparency, audit trails, and release controls.
  • Define KPIs for adoption, workflow completion, time savings, quality, customer satisfaction, risk reduction, operational efficiency, and revenue impact.
  • Define AI-specific metrics such as task success rate, acceptance rate, escalation rate, hallucination rate, user trust, cost per successful outcome, and time saved.
  • Use evaluation approaches such as golden datasets, offline evals, human review, LLM-as-judge where appropriate, regression checks, shadow mode, staged rollouts, and online experiments.

What Success Looks Like in the First 6 to 12 Months

  • A clear AI product roadmap is defined, prioritized, and aligned with company strategy.
  • High-value AI and automation opportunities are translated into MVPs, measurable outcomes, and risk-managed launch plans.
  • At least one AI-enabled capability, intelligent workflow, data-driven insight, or integration-driven experience is launched, piloted, or meaningfully advanced toward production.
  • Customer evidence from interviews, usage data, support trends, or adoption metrics shows that shipped capabilities are solving real workflow problems.
  • A practical evaluation approach is established so AI quality, safety, and regression risk are visible to the team.
  • AI product practices improve across guardrails, release readiness, evaluation, human-in-the-loop design, observability, and post-launch monitoring.
Requirements:

Required Qualifications

  • 7+ years of product management experience in B2B SaaS, workforce technology, compliance software, transportation technology, enterprise workflow software, data products, automation products, or a related domain.
  • 1 to 2+ years shipping AI/ML, generative AI, intelligent automation, conversational analytics, agentic workflows, or data-driven workflow products to real users.
  • Ownership of at least one AI-powered or agent-based capability, such as a co-pilot, assistant, intelligent automation, multi-step workflow, conversational interface, recommendation system, or AI-assisted workflow.
  • Strong technical fluency in LLMs, prompt design, context engineering, retrieval-augmented generation, structured outputs, agent frameworks, evaluation methods, and cost, latency, quality, and safety tradeoffs.
  • Experience defining product strategy, requirements, user stories, acceptance criteria, success metrics, rollout plans, and post-launch iterations.
  • Strong product judgment, including the ability to decide when AI is appropriate and when deterministic workflow automation is better.
  • Experience with sensitive data, regulated workflows, compliance-heavy products, high-trust customer environments, or enterprise systems.
  • Strong analytical, written, and verbal communication skills.
  • Bachelor’s degree in business, computer science, engineering, data science, human-computer interaction, or a related field. Equivalent experience will also be considered.

Preferred Qualifications

  • Experience with employment screening, drug screening, employment verification, credentialing, license or certification tracking, continuous monitoring, audit readiness, regulated operations, document management, healthcare, transportation, employee life cycle, or compliance-heavy workflows.
  • Experience launching AI-powered features, agents, copilots, workflow automation, recommendation systems, or data-driven decision support into production.
  • Experience designing conversational or natural-language interfaces over complex enterprise data.
  • Experience designing or operating LLM or agent evaluation systems, including golden sets, regression evals, LLM-as-judge, online experimentation, or human review workflows.
  • Familiarity with Claude, ChatGPT, Amazon Bedrock, Azure OpenAI, GitHub Copilot, Cursor, LangChain, LlamaIndex, vector databases, MCP-based connectors, LangGraph, AutoGen, CrewAI, Bedrock Agents, or AI evaluation tools.
  • Working understanding of embeddings, retrieval architectures, data quality issues, permissions, enterprise identity, and enterprise data access patterns.
  • Experience with API-driven platforms, integrations, partner ecosystems, data contracts, workflow orchestration, privacy, security, auditability, or trust-sensitive workflows.

The Profile We Are Looking For

  • Strategic but hands-on: You can shape a roadmap and still get into workflows, edge cases, acceptance criteria, launch readiness, and post-launch learning.
  • AI-aware, not AI-hyped: You are excited about AI but realistic about quality, risk, cost, privacy, reliability, model limitations, and customer trust.
  • Technically fluent: You can discuss APIs, data flows, integrations, permissions, model behavior, evaluation, observability, and tradeoffs with engineering.
  • Production-minded: You understand that AI quality must be tested, monitored, supported, and improved after launch.
  • Domain-curious: You are willing to learn the details of regulated workflows, operational edge cases, and customer processes.
  • Customer-obsessed: You care about whether the product solves the customer’s problem, not just whether the feature shipped.
  • High ownership: You create structure, make tradeoffs visible, and move work forward.

Why Join AccuSourceHR

  • Help shape practical AI-enabled products with real customer value.
  • Work on AI, automation, integrations, and data-driven insights in complex business workflows.
  • Partner directly with executive product leadership in a visible, high-impact role.
  • Join a company with an established reputation, long-term customers, and meaningful room for product innovation.

Benefits:

  • Medical (with company contribution)
  • Dental (with company contribution)
  • Vision
  • Employer paid Life Insurance and Long-Term Disability
  • Short-Term Disability
  • 401(k) (with company match)
  • Paid holidays
  • Paid time off (PTO)
  • Sick Time
  • Pet insurance

Physical Requirements:

  • Must have a dedicated and ergonomic workspace at home conducive to focused work.
  • Access to a stable and reliable high-speed internet connection.
  • Adequate lighting and minimal background noise to support professional video calls and meetings.
  • Ability to lift and carry up to 5 pounds occasionally, for tasks such as setting up a workstation or equipment.
  • The ability to work comfortably and effectively in a home environment that meets ergonomic standards, including proper seating and desk setup.

Equal Employment Opportunity:AccuSourceHR, Inc, provides equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetic information, pregnancy, gender identity, sexual orientation, status as a Vietnam-era, special disabled veteran or other veteran, or any other status or characteristic protected by applicable federal, state and/or local laws.
AccuSourceHR, Inc. reserves the right to modify, interpret, or apply the job description as needed. This job description is for informational purposes only and should not be construed as an offer or guarantee of employment.
Any offer of employment is conditional upon the successful completion of a background investigation and drug screening.
By submitting your application for and/or accepting this position, you acknowledge and agree that, if selected, you will be required to electronically sign certain employment-related documents upon commencing your position. This may include, but is not limited to, the offer letter, employment agreement, and other necessary forms.
This job description is not designed to cover or contain all job duties required of the employee. There may be additional activities, duties and/or responsibilities that are required for this position that are not listed in this job description.