Scale Engineer

Software Engineer AI Team

Backend Engineer · Mid · Full Time

PL-Warsaw-Lixa CUSD 165k – 230k1d ago
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Role

What you'll do.

Join Snowflake's AI team as a Software Engineer to build scalable, production-quality platforms for the agentic enterprise. This role requires 3+ years of backend engineering experience with languages like Go, Java, C++, or Python, combined with strong expertise in building SDKs, web service APIs (REST/gRPC), and MLOps practices. You'll collaborate across research, engineering, and business teams to develop innovative AI solutions while mentoring less experienced engineers and shaping the future of how work gets done in the AI-native era.

Responsibilities

  • Platform Development and Optimization: Develop, deploy, and optimize new AI-native platforms and services while improving existing Snowflake AI functionalities. Participate in all stages of the software development lifecycle, from architecture and implementation through production serving and performance optimization.
  • Creative Problem Solving: Tackle complex, ambiguous technical challenges by formulating problems from abstract information and designing optimal solutions that scale across the Snowflake ecosystem. Apply experimental mindset to rapidly prototype and test emerging AI capabilities.
  • Cross-functional Collaboration: Work closely with research teams, engineering organizations, product management, and business stakeholders to understand requirements, shape product development strategy, and align technical decisions with short and long-term organizational goals.
  • Mentorship and Leadership: Mentor less experienced engineers, researchers, and product managers, fostering a collaborative culture of knowledge-sharing. Lead technical discussions and take ownership of initiatives when required while maintaining individual contributor excellence.
  • Technical Communication: Articulate complex technical concepts, research findings, and architectural decisions clearly to both technical and non-technical leadership, ensuring alignment on objectives and outcomes.

Qualifications

What we look for.

Technical

  • Backend Programming Languages

    3+ years of professional experience writing production-quality, scalable code using backend languages such as Go, Java, C++, or Python. Demonstrated proficiency in building performant systems that handle complex distributed workloads.

  • API Architecture and SDK Development

    Professional-level expertise in designing and implementing SDKs, web service APIs (REST and gRPC protocols), and integration frameworks. Strong understanding of API design patterns, versioning strategies, and backward compatibility considerations.

  • Software Engineering Best Practices

    Solid command of industry-standard practices including code quality standards, comprehensive testing strategies (unit, integration, end-to-end), version control systems (Git), CI/CD pipelines, containerization (Docker), orchestration platforms (Kubernetes), automation frameworks (Jenkins), and agile development methodologies.

  • MLOps and Model Deployment

    Hands-on experience with MLOps practices, including model training pipeline orchestration, model deployment strategies, monitoring, versioning, and lifecycle management. Familiarity with tools and frameworks commonly used in production ML environments.

Education

  • Bachelor's Degree in Technical Field

    BSc required in a technical discipline such as Computer Science, Artificial Intelligence, Machine Learning, Data Science, Physics, Mathematics, or equivalent engineering field.

  • Advanced Degree (Preferred)

    MSc or PhD in a technical field is a significant asset, particularly in AI/ML or related disciplines. Demonstrates research orientation and depth of expertise in complex technical domains.

Experience

  • Backend Systems Development

    Minimum 3+ years of professional software engineering experience developing scalable backend systems, distributed services, or cloud infrastructure. Track record of shipping production systems used at scale.

  • Problem Formulation and Research Mindset

    Demonstrated ability to formulate well-structured technical problems from abstract or ambiguous requirements. Experience approaching open-ended technical challenges with curiosity and systematic problem-solving skills.

  • Independent and Collaborative Work

    Proven ability to autonomously own technical decisions and deliver organized solutions while thriving in team environments. Experience working across multiple teams and occasionally taking on leadership responsibilities for specific technical initiatives.

Skills

Required

  • Go

    Production-level expertise in Go programming for building scalable, concurrent backend systems and cloud-native applications.

  • Java

    Strong proficiency in Java for enterprise-scale backend development, understanding of frameworks, concurrency patterns, and JVM performance optimization.

  • C++

    Advanced capability in C++ for performance-critical components, systems programming, and low-latency applications.

  • Python

    Strong Python skills for scripting, data processing, ML integration, and rapid development of backend services and tools.

  • REST API Design

    Expertise in designing RESTful APIs following HTTP specifications, proper status codes, resource modeling, and stateless communication patterns.

  • gRPC

    Professional experience implementing gRPC services for high-performance, low-latency inter-service communication using protocol buffers.

  • Docker

    Practical knowledge of containerizing applications, creating optimized Dockerfiles, managing image registries, and implementing container security best practices.

  • Kubernetes

    Hands-on experience orchestrating containerized applications in Kubernetes environments, including deployment strategies, scaling, and operational management.

  • CI/CD Pipelines

    Proficiency in designing and maintaining continuous integration and continuous deployment pipelines using tools like Jenkins, ensuring automated testing and reliable deployments.

  • Git Version Control

    Strong command of Git for collaborative development, including branching strategies, pull requests, code reviews, and resolving merge conflicts.

Preferred

  • MLOps Tools and Frameworks

    Nice to have

    Experience with MLOps platforms and tools such as Airflow, Kubeflow, DVC, MLflow, or similar technologies for orchestrating ML workflows and managing model lifecycles.

  • ML Model Deployment

    Nice to have

    Hands-on experience deploying machine learning models to production, managing model versioning, monitoring inference performance, and scaling serving infrastructure.

  • Cloud Platforms

    Nice to have

    Experience working with major cloud providers (AWS, Azure, GCP) for building and deploying scalable backend services and infrastructure.

  • Data Warehousing Concepts

    Nice to have

    Familiarity with data warehouse architecture, OLAP systems, and analytical databases relevant to cloud data platforms and analytics use cases.

  • Distributed Systems Design

    Nice to have

    Knowledge of distributed systems principles including consistency models, fault tolerance, distributed consensus, and scaling strategies.

  • Agile Development Practices

    Nice to have

    Experience working in agile environments including sprint planning, daily standups, retrospectives, and iterative delivery methodologies.

  • System Architecture and Design Patterns

    Nice to have

    Understanding of microservices architecture, event-driven systems, and modern design patterns for building scalable and maintainable backend systems.

Tech stack

Languages

GoJavaC++Python

Frameworks

REST FrameworksgRPCAgile Development Frameworks

Databases

Snowflake Data WarehouseDistributed Data Stores

Tools

DockerKubernetesJenkinsGit

Other

MLOps PracticesSDK DevelopmentAPI Protocol BuffersSoftware Engineering Best Practices

Compensation

Pay and benefits.

Base·USD 165,000 – 230,000

Equity·Stock options

Benefits

  • Competitive Compensation and Equity

    Comprehensive salary package aligned with market standards for senior backend engineers, stock options providing equity participation in Snowflake's growth as a public company.

  • Health and Wellness Coverage

    Comprehensive health insurance (medical, dental, vision), mental health support, wellness programs, and fitness benefits for employee wellbeing.

  • Retirement Planning

    401(k) retirement plan with company matching, ensuring long-term financial security and retirement readiness.

  • Professional Development

    Opportunities for continuous learning through conferences, training programs, certifications, and internal knowledge-sharing initiatives in AI/ML domains.

  • Flexible Work Arrangements

    Work-life balance support including flexible schedules, potential remote work opportunities, and collaboration tools for distributed teamwork.

  • Career Growth Opportunities

    Clear advancement paths from individual contributor to staff engineer, management, and leadership roles within a rapidly growing technology company.

  • Mentorship and Collaboration

    Access to senior engineers, researchers, and thought leaders within Snowflake's organization for continuous skill development and knowledge transfer.

  • Innovative Technology Environment

    Opportunity to work on cutting-edge AI, machine learning, and cloud computing technologies at scale with real business impact.

Process

Interview steps.

  1. 01

    Recruiter Screening Call

    Initial 30-minute conversation with a technical recruiter to discuss your background, career goals, understanding of Snowflake's AI initiatives, and alignment with the role requirements.

  2. 02

    Technical Phone Screen

    45-minute technical interview with a senior engineer assessing your proficiency in backend programming languages, system design thinking, and problem-solving approach through live coding or architecture discussion.

  3. 03

    System Design Interview

    60-minute session focused on architectural thinking, scalability considerations, distributed systems knowledge, and your ability to design solutions for complex AI/ML serving infrastructure challenges.

  4. 04

    Coding Technical Assessment

    Comprehensive coding challenge evaluating your ability to implement efficient algorithms, write clean production-quality code, and handle edge cases in backend systems development.

  5. 05

    ML/MLOps Depth Discussion

    Technical conversation with an engineer specializing in MLOps and AI infrastructure to assess your experience with model deployment, serving infrastructure, and operational excellence in ML systems.

  6. 06

    Senior Engineer/Manager Round

    Conversation with a team lead or manager discussing cross-functional collaboration, mentorship philosophy, leadership approach, and long-term career aspirations at Snowflake.

  7. 07

    Leadership Round

    Optional final interview with a director or senior leadership to assess cultural fit, alignment with Snowflake's AI-native vision, and your potential impact on the organization.

Full posting

Original listing.

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.

Your journey as a Software Engineer

Working in our team you will:

  • Think creatively to find optimal solutions to our complex, often ambiguous problems

  • Participate in all stages of developing and serving new platforms for various AI solutions and improving existing Snowflake’s functionalities in the AI domain

  • Work closely with other research, engineering, and business teams to understand and shape the short and long-term product development strategy

  • Serve as a mentor to less experienced engineers, researchers, and product managers

Ideal candidate

  • 3+ years of experience writing production-quality scalable code using backend languages (preferred Go, Java, C++, Python)

  • BSc in a technical field (AI/ML, CS, DS, Physics, Math, etc), MSc/PhD is a plus

  • Professional level in building SDKs / web service APIs (REST/ gRPC)

  • Experience with software engineering best practices (programming, testing, version control, CI/CD, docker/Kubernetes, Jenkins, agile development, etc)

  • High levels of curiosity and eager enthusiasm for open-ended problems. Experience and interest in problem formulation based on relatively abstract information

  • Ability to articulate results and complex concepts to leadership

  • Must be able to produce solutions independently in an organized manner, work in a team, and also be able to lead a team when required

  • Hands-on experience in the MLOps field (e.g., deploying ML models) will be a strong asset.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.

How do you want to make your impact?

For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

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