Product Engineer
DoiT International
full-time
Posted on:
Location Type: Remote
Location: Israel
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About the role
- Full-lifecycle problem solving
- Own problems end-to-end: from understanding user pain, through solution design, implementation, release, measurement, and iteration - not just the coding step.
- Engage directly with customers and internal domain experts to build deep empathy for the workflows and challenges of cloud operators and FinOps practitioners.
- Translate ambiguous problem spaces into clear, thin-sliced increments that can be shipped, measured, and learned from quickly.
- Use AI tools daily to amplify your own engineering work - coding, analysis, research, and prototyping.
- Design and build AI-powered features as a default approach: intelligent recommendations, automated insights, natural-language interfaces, and predictive capabilities for cloud cost optimization.
- Make informed decisions on model selection, prompt engineering, latency/accuracy/cost tradeoffs, and responsible AI considerations as a core part of your engineering practice.
- Operate with a bias toward action: prototype rapidly, ship frequently, and validate ideas through real customer usage rather than prolonged planning cycles.
- Build experiments and MVPs that generate measurable learning - and use those learnings to decide what to invest in next.
- Maintain high engineering standards without letting perfection slow down delivery; know when to take deliberate shortcuts and when to invest in durability.
- Build across the full stack - backend services, APIs, data pipelines, and frontend interfaces - whatever the problem demands.
- Work with cloud-native billing, usage, and operational data from AWS, GCP, and Azure to build cost optimization and governance capabilities.
- Develop solutions that operate across Kubernetes environments, data cloud platforms, and broader multi-cloud infrastructure.
- Build state-of-the-art solutions for Generative AI observability and FinOps - enabling customers to understand, monitor, and optimize the cost and performance of their AI/ML workloads across cloud environments.
- Take full ownership of the solutions you ship - including reliability, user experience, and measurable outcomes.
- Define what success looks like for your work using clear metrics: adoption, activation, workflow improvement, cost savings delivered, and customer-reported impact.
- Participate in customer conversations and feedback loops to continuously validate direction and surface new opportunities.
Requirements
- 5+ years of professional software engineering experience, with demonstrated ability to deliver complete products or features end-to-end.
- AI-first mindset - you actively use AI tools to accelerate your work and instinctively look for opportunities to embed AI into what you build.
- Strong full-stack engineering capability: you can work effectively across backend, frontend, APIs, and data layers without being confined to a single technology or language.
- Solid understanding of public cloud platforms (AWS, GCP, and/or Azure) - including core concepts like compute, networking, IAM, Kubernetes, and billing/cost structures.
- Product-oriented thinking: you care as much about why you’re building something and whether it works for users as you do about how it’s built.
- Comfort with ambiguity and fast-changing priorities - you thrive when you need to figure out the right problem to solve, not just the right solution.
- Strong customer empathy and communication skills -- you can engage with technical practitioners, synthesize feedback, and explain complex ideas clearly.
- Excellent communication skills in English, both written and verbal.
- Self-motivated, resourceful, and effective in a remote, fast-moving team environment.
Benefits
- Unlimited Vacation
- Flexible Working Options
- Health Insurance
- Parental Leave
- Employee Stock Option Plan
- Home Office Allowance
- Professional Development Stipend
- Peer Recognition Program
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
full-lifecycle problem solvingAI toolsbackend servicesAPIsdata pipelinesfrontend interfacesKubernetescloud-native billingcost optimizationGenerative AI
Soft Skills
customer empathycommunication skillsproduct-oriented thinkingcomfort with ambiguityself-motivatedresourcefuleffective in remote teamsengagement with technical practitionerssynthesizing feedbackexplaining complex ideas