Kamiwaza is an enterprise AI orchestration platform that organizations deploy on-premises or in their own cloud to run inference, connect distributed data sources, build knowledge graphs, and orchestrate multi-agent AI workflows. The platform is Kubernetes-based, silicon-agnostic, and built for environments where security and data sovereignty are non-negotiable.
Kamiwaza needs a dedicated product leader who can translate customer problems into clear priorities, validated solutions, and coherent releases without becoming a feature-request router. This is a hands-on individual contributor role focused on product strategy, discovery, prioritization, and cross-functional alignment. You will partner deeply with engineering, design, product marketing, and go-to-market, and you will use AI tooling aggressively to increase throughput and decision quality.
The Unique Challenge: Fast Internal Build Cycles, Deliberate Customer Releases
Kamiwaza’s engineering team is moving toward highly AI-assisted development, which compresses internal cycle times. But Kamiwaza ships an on-prem product with slower, more deliberate customer-facing release cycles. This role lives in that tension. Engineering may be able to build quickly, but each release still needs to be worth the customer’s effort to upgrade. You will help ensure that fast internal development turns into coherent, valuable, low-regret releases.
Core Mission
Own product strategy, discovery, and release discipline for Kamiwaza’s enterprise AI orchestration platform — translating real customer problems into a coherent, outcome-driven roadmap that engineering, sales, marketing, and federal stakeholders can rally around.
Own and evolve the product vision: where the product is going and why.
Define and maintain a strategy that connects customer problems to business outcomes — revenue, retention, expansion, risk reduction, and time-to-value.
Translate strategy into outcome-based roadmaps and priorities, not feature lists.
Establish product principles and decision filters to maintain focus in a dynamic environment.
Drive roadmap clarity across engineering, sales, marketing, support, and leadership.
Actively identify and communicate what not to build — maintain a clear view of market antipatterns and short-lived trends.
Spend significant time with customers and prospects through interviews, workflow observation, and feedback loops.
Build strong working relationships with commercial users and the Fed Team to understand workflows, constraints, and high-value use cases.
Identify, size, and prioritize problems worth solving using qualitative and quantitative evidence.
Run discovery practices such as prototypes, usability tests, concierge validation, and solution testing before committing major engineering effort.
Maintain a living, ranked problem backlog and defend priorities with evidence.
Work as a true partner to engineering leadership, co-owning outcomes rather than handing off requirements.
Create clarity on the problem, the customer, and the desired outcome — while engineering owns implementation details and technical design.
Frame problems at the right altitude for an AI-native engineering team: specific enough to guide action, not so prescriptive that it blocks better solutions.
Lead problem framing, discovery readouts, solution discussions, and launch readiness conversations.
Be accountable for product clarity, user usefulness, and experience quality — without acting as the sole designer of record.
Use lightweight prototypes, workflow sketches, and AI-assisted mockups to test ideas, accelerate discovery, and communicate intent.
Partner with engineering and design support to refine workflows, edge cases, error handling, and interaction patterns.
Build trusted relationships with commercial customers and the Fed Team to understand workflows, constraints, and mission-critical use cases.
Translate Federal-adjacent needs — security, auditability, permissions, deployment models, procurement realities — into product priorities without letting any one category dominate the roadmap.
Manage commitments carefully and create alignment with Sales, Marketing, Partnerships, and Fed stakeholders on what is committed, exploratory, or deferred.
Own the release-planning rhythm from a product perspective, ensuring each release is a coherent bundle of customer value.
Own the dogfooding program so pre-release builds are used in realistic ways by the right internal teams.
Use on-prem release realities to improve prioritization, sequencing, and launch quality.
Partner with Sales, Marketing, and Partnerships by providing product truth, customer problem definitions, target use cases, proof points, and roadmap context.
Support discovery motions, demo narratives, and launch readiness with accurate product inputs and reviews.
Contribute to release notes, enablement material, and customer-facing explanations as the product subject-matter lead.
Absorb signal from hardware and channel partners whose field teams surface customer pain points early.
Use AI tools and agents as a force multiplier across research synthesis, note capture, feedback analysis, competitive scanning, draft artifacts, lightweight prototyping, and analytics.
Create lightweight automations where they create clear leverage.
Apply AI responsibly, with strong judgment around security, confidentiality, and quality control.
First 180 Days — Mandate for Success
Days 0–60: Foundation and Discovery
Achieve deep, hands-on mastery of the Kamiwaza platform — capabilities, APIs, deployment patterns, and differentiators.
Build strong working relationships with engineering leadership, sales, and the Fed Team.
Establish a repeatable discovery cadence: customer interviews, workflow observation, and feedback loops with both commercial and federal stakeholders.
Audit the current roadmap and backlog; assess priorities against customer evidence and identify top gaps.
Days 61–120: Strategy and Cadence
Deliver a clear, communicated product vision and strategy that engineering, sales, marketing, Fed, and partnerships can rally around.
Establish a healthy operating rhythm with engineering and go-to-market that turns requests into validated opportunities while protecting focus.
Lead at least one full discovery cycle from problem identification through solution validation before build commitment.
Shape at least one monthly release as a coherent bundle of customer value, with a clear upgrade rationale.
Days 121–180: Scale and Impact
Demonstrate measurable improvements in customer outcomes: adoption, time-to-value, or retention signals from recent releases.
Establish a product system that scales through clear prioritization, lightweight artifacts, and transparent decisions.
Create release-planning discipline where each monthly release is demonstrably worth the customer’s upgrade effort.
Enable go-to-market teams with accurate product truth, target use cases, and roadmap context that improves pipeline and expansion conversations.
Expected Behaviors
You will be successful here if you consistently:
Start with the problem and treat solutions as hypotheses until validated.
Seek truth over harmony — use evidence and surface hard tradeoffs early.
Optimize for outcomes rather than output.
Partner deeply rather than relying on handoffs.
Say no with clarity and empathy when focus requires it.
Communicate relentlessly through crisp writing, clear decisions, and visible tradeoffs.
Use AI as leverage, not as a substitute for judgment, customer contact, or cross-functional collaboration.
What This Role Is Not
Not a ticket scribe.
Not a feature-factory operator.
Not a project manager whose main value is status tracking.
Not an approval bottleneck for engineering.
Product Leadership Experience
8+ years in product management or product leadership, including strong hands-on IC experience.
Proven experience building B2B technical products — platform, infrastructure, developer, data, AI, security, or workflow-heavy products.
Strong track record of continuous discovery and shipping products that improved measurable customer and business outcomes.
Experience as an early or first product hire at a growth-stage company is a strong plus.
Technical Fluency
You do not need to be the deepest expert in every area, but you need enough breadth to ask good questions, understand tradeoffs, and make sound prioritization decisions across:
Infrastructure and deployment
Inference and model management
Data systems and knowledge representation
Security and authorization
Agentic AI and orchestration
Platform extensibility and APIs
Core Competencies
Comfort operating in ambiguity, speed, and imperfect information.
Ability to engage directly with customers through interviews, demos, workflow mapping, and priority negotiation.
Strong written and verbal communication — this company runs on writing.
Demonstrated ability to partner deeply with engineering and make sound tradeoff decisions.
Strong product sense, including the ability to use lightweight prototypes or workflow artifacts to accelerate learning.
Demonstrated ability to use AI tooling productively and responsibly in research, synthesis, communication, analysis, and prototyping.
Experience with Federal-adjacent requirements and regulated environments.
Experience supporting enterprise sales motions, POVs, pilots, enablement, and roadmap communication.
Familiarity with product analytics, experimentation, and SQL.
Background in on-prem, installed, or self-hosted B2B software.
Prior work on developer platforms, infrastructure software, or extensible platforms.
Experience running beta, early-access, or dogfooding programs.
Purpose & Impact: Be a key contributor to the GenAI revolution, shaping how enterprises adopt next-generation technology.
Remote-First Culture: Based in Colorado, but work from anywhere with the tools and support you need.
Expert Founders with Successful Exits: Our leadership team brings experience and a relentless enthusiasm for GenAI innovation.
High-Autonomy Environment: Flat organizational structure, transparent communication, and minimal red tape.
Competitive Compensation & Equity: Own a piece of our high-potential, well-funded startup.
Comprehensive Benefits: Health coverage, remote workspace support, and more.
We're a small, driven team building a platform that makes GenAI deployment feel like magic.
Our approach: curious, humble, but relentless.
We're fun, kind, and exceptional—serious about making an impact but never taking ourselves too seriously.
We operate with high urgency but think for the long term—action creates clarity.
Ready to build the foundation of the GenAI revolution? Please include a short write-up of a customer problem you solved end-to-end and a link to any reusable asset or press release that came out of it.
P.S. If you use GenAI to craft your application, we'll probably find out—and we'd love to learn more about how you did it!
This role offers a base salary between $185,000 and $250,000, plus equity and benefits. Actual compensation will reflect an individual’s experience, impact, and location. Our benefits include low-deductible medical plans, flexible time off, and supportive family leave policies.
