Interested in this AI Product Manager role at Blueprint Technologies?
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About This Role
About Blueprint
Blueprint is a technology solutions firm headquartered in Bellevue, Washington, with teams across the United States. We help organizations turn complex challenges into meaningful outcomes by connecting strategy and execution across AI, cloud, data, product development, and emerging technology.
Our culture is built by people who care deeply about doing exceptional work. We set high standards, take ownership, and continually challenge ourselves and one another to be better. We work hard, support each other, and take genuine pride in what we deliver for our clients, partners, and teams.
At Blueprint, you'll work alongside talented people with different experiences, expertise, and perspectives. You'll have opportunities to take on meaningful challenges, expand your skills, and see the impact of what you build.
Bring your perspective. Raise the standard. Build what matters.
In this role
You will build applied AI and platform solutions that transform manual, repetitive, and human-driven operational processes into reliable automated and agent-driven systems. You will identify opportunities for automation, develop AI agents and orchestration workflows, and turn successful prototypes into secure, observable, production-ready services. Working across Azure, .NET, C#, Python, React, SQL, and modern AI technologies, you will build integrations, APIs, evaluation frameworks, and automation infrastructure while partnering directly with end users and cross-functional stakeholders. This role is well suited for an engineer who is comfortable operating in ambiguity, understands both traditional software engineering and non-deterministic AI systems, and can balance experimentation with production-quality engineering standards.
Responsibilities
- Identify high-friction operational workflows, quantify the current-state cost, and design automated or agent-driven solutions that improve efficiency, reduce errors, and increase throughput.
- Build AI agents and intelligent workflows using Azure AI Foundry, Copilot Studio, Microsoft Agent Framework, MCP, and related frameworks.
- Design multi-step tool use, orchestration, and human-in-the-loop workflows for agentic applications.
- Replatform prototypes and proofs of concept into secure, scalable, observable, and supportable production services.
- Design and develop RESTful APIs, tool/function endpoints, and backend services using Azure App Services.
- Apply prompt engineering, grounding, retrieval, Azure AI Search, and evaluation practices to improve AI system quality and reliability.
- Build evaluation and quality infrastructure for AI systems, including offline evaluation sets, CI regression gates, drift detection, and release criteria.
- Develop observability for AI and agentic systems, including quality, cost, latency, tool-call outcomes, and rollback capabilities.
- Build integrations between internal and external systems while maintaining appropriate human review, approval, and intervention points.
- Implement secure authentication and authorization using Entra ID, including workload identity, least-privilege access, and delegated permissions.
- Support privacy, security, accessibility, responsible AI, and compliance assessments for AI-powered solutions.
- Use Azure DevOps for source control, CI/CD, automated testing, release management, and work tracking.
- Partner with engineers, program managers, stakeholders, and end users to understand operational processes and translate them into effective technical solutions.
- Participate in code reviews, unit testing, Agile ceremonies, troubleshooting, and debugging across distributed and AI-dependent systems.
- Evaluate emerging AI and agent technologies and provide practical recommendations for their application.
- Document workflow architectures, agent behavior and boundaries, integration contracts, and system designs.
Qualifications
- Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent professional experience.
- 3+ years of professional software development experience, with a focus on cloud-based applications.
- Strong proficiency with .NET, C#, Python, and SQL for backend development.
- Hands-on experience building with LLMs and AI services, including prompt engineering.
- Experience taking at least one AI-powered feature, agent, or automation into production or near-production and being able to discuss the technical implementation in depth.
- Demonstrated experience automating real-world workflows through process automation, orchestration, integrations, or agentic tooling.
- Strong knowledge of Azure App Services, Azure SQL, Logic Apps, Copilot Studio, Azure AI Foundry, and Azure AI Search.
- Experience using Azure DevOps for version control, build automation, release management, and project tracking.
- Experience designing secure applications using Entra ID for authentication and authorization.
- Strong understanding of SQL database design, optimization, and querying.
- Strong problem-solving, debugging, and troubleshooting abilities across code, data, configuration, and AI/model behavior.
- Ability to collaborate effectively with both technical and non-technical stakeholders.
- Ability to work directly with end users, gather requirements, provide technical guidance, and iterate based on feedback.
Preferred Qualifications
- Prior experience with the client's organization and familiarity with its development practices, technologies, and internal systems.
- Experience with agent frameworks and orchestration, such as Microsoft Agent Framework, Semantic Kernel, LangGraph, or MCP.
- Experience with tool design and multi-agent coordination.
- Experience developing LLM evaluation harnesses, including offline evaluation sets, LLM-as-judge approaches, and automated quality gates.
- Demonstrated ability to take an internal prototype, hack, or proof of concept and turn it into a supported production service.
- Experience replacing legacy manual processes through automation, particularly where organizational workflows are complex.
- Front-end development experience with React.
- Experience with large-scale distributed systems and multiple integration points.
- Familiarity with responsible AI practices and enterprise compliance review processes.
Compensation
At Blueprint, we strive to offer competitive pay that reflects the value of our team members. Compensation for this role is influenced by a variety of factors, including skills, education, responsibilities, experience, and geographic market.
For candidates based in Washington State, the anticipated compensation range is $105000 - $115000 USD annually Please note that we typically do not hire new employees at the top of the posted range. Actual starting pay will be determined based on experience, skills, and internal equity. The final compensation and job title may vary depending on the selected candidate's qualifications.
Location: Remote EST hours, ideally in the Charlotte, NC area
Benefits
Blueprint believes that healthy, supported employees do their best work. Eligible employees have access to a comprehensive benefits package that may include:
- Medical, dental, and vision coverage
- Flexible Spending Account (FSA)
- 401(k) retirement plan
- Competitive paid time off
- Parental leave
- Professional growth and development opportunities
Benefits and eligibility may vary based on role, employment status, and location.
Equal Employment Opportunity
Blueprint Technologies, LLC is an equal opportunity employer. We consider qualified applicants without regard to race, color, religion, sex, pregnancy, childbirth or related medical conditions, sexual orientation, gender identity or expression, national origin, ancestry, age, disability, genetic information, marital or familial status, military or veteran status, citizenship status, or any other characteristic protected by applicable law.
Applicant Accommodations
If you need a reasonable accommodation to participate in any part of the application or interview process, please contact [email protected].
Salary Context
This $105K-$115K range is in the lower quartile for AI Product Manager roles in our dataset (median: $193K across 99 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 9,653 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At Blueprint Technologies, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $220,200 based on 862 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($110K) sits 50% below the category median. Disclosed range: $105K to $115K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Blueprint Technologies AI Hiring
Blueprint Technologies has 1 open AI role right now. They're hiring across AI Product Manager. Based in Charlotte, NC, US. Compensation range: $115K - $115K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
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