Hungry, Humble, Honest, with Heart.

The Opportunity

We are looking for a passionate full-stack engineer with a builder’s mindset for applied AI to design and deliver intelligent, scalable systems that solve real business problems. This role offers the opportunity to work on production-grade AI features and full-stack applications, leveraging modern AI architectures, cloud technologies, and microservices.

You will contribute to critical internal and SaaS applications, applying Generative AI and machine learning to enhance workflows, automate processes, and improve engineering productivity. This is a hands-on engineering role focused on building reliable, production-ready systems that integrate deeply with real products and workflows, not prompt-only experimentation.

This is an opportunity to work on hard technical problems at scale, collaborate with highly capable engineers, and take end-to-end ownership of impactful systems in a fast-paced and innovation-driven environment.

About the Team

The role is part of the SaaS Engineering group at Nutanix, responsible for building and operating intelligent internal platforms and full-stack web services that support critical business and engineering workflows. The team develops scalable applications and AI-driven capabilities that integrate across cloud services, enterprise systems, and internal tools.

The team is globally distributed across the US and India and operates in a collaborative environment focused on ownership, engineering excellence, and continuous improvement. Engineers on the team have strong autonomy and are empowered to design, build, and operate systems end-to-end while contributing to the evolution of the platform and engineering practices.

You will report to an Engineering Manager and work closely with engineers, product managers, and stakeholders across teams to deliver scalable, reliable, and intelligent solutions.

Your Role

• Develop and maintain full-stack applications using the MERN stack (MongoDB, Express, React, Node.js), including frontend, backend services, and REST APIs.
• Design, build, and own production-grade AI systems, including agentic workflows, retrieval systems (RAG), orchestration logic, and service integrations.
• Apply Generative AI and machine learning to solve real user problems, and integrate AI capabilities into existing tools and platforms.
• Take end-to-end ownership of features, including design, implementation, deployment, monitoring, evaluation, and continuous improvement.
• Design scalable backend services and microservices, and integrate with enterprise and cloud platforms such as Salesforce, Jira, Slack, and other internal systems.
• Ensure reliability, performance, and maintainability of systems through strong engineering practices, monitoring, and proactive issue resolution.
• Collaborate with cross-functional teams to translate requirements into scalable technical solutions and communicate technical concepts clearly to stakeholders.
• Participate in architecture discussions, design reviews, and code reviews, and contribute to improving engineering standards and system scalability.

What You Will Bring

• 1-3 years of full-stack development experience using the MERN stack, building scalable, production-grade applications.
• Proven experience building and deploying AI-powered systems beyond prompt engineering, including backend integration, orchestration, and production ownership.
• Strong understanding of LLM-based architectures, including retrieval-augmented generation (RAG), agents, tool/function calling, and their real-world trade-offs.
• Solid software engineering fundamentals, including system design, data structures, and algorithms, and building reliable distributed systems.
• Strong proficiency in JavaScript, Node.js, Express, and React, with experience building REST APIs and scalable backend services.
• Experience working with SQL/NoSQL databases (preferably MongoDB), microservices architectures, and cloud platforms such as AWS.
• Experience designing evaluation strategies, monitoring AI systems, and improving reliability, accuracy, and operational performance.
• Strong problem-solving skills, ownership mindset, and ability to independently drive features from concept to production.
• Bachelor’s or Master’s degree in Computer Science or a related field, or equivalent practical experience.

Work Arrangement

Hybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in-person collaboration. In locations where our workplace policy applies (i.e. San Jose, Durham, Mexico City, Bangalore, Pune, Hoofddorp, Belgrade, Barcelona, Singapore, Sydney and Tokyo), employees are expected to work onsite a minimum of 3 days per week to foster collaboration, team alignment, and access to in-office resources. Workplace type may vary based on location and team requirements. Please speak with your recruiter for details. Additional team-specific guidance and norms will be provided by your manager.

The pay range for this position at commencement of employment is expected to be between USD $ 0 and USD $ 0 per year.

However, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements, including a sign-on bonus, restricted stock units, and discretionary awards in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave), dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

If hired, employee will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors. Our application deadline is 40 days from the date of posting. In good faith, the posting may be removed prior to this date if the position is filled or extended in good faith.

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