Software Engineer - AIM Virtualization
Backend Engineer · Mid · Full Time
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Role
What you'll do.
Join Snowflake's AIM Virtualization team as a Software Engineer to pioneer database virtualization technology that eliminates costly data platform migrations. This role leverages AI-driven software synthesis to build innovative solutions at the intersection of database internals and practical application, requiring deep expertise in SQL, database systems, and functional programming with 2-7 years of experience.
Responsibilities
- AI-Driven Platform Development: Participate in full-stack AI-based development across the AIM Virtualization platform, spanning syntactic and semantic analysis, wire protocols implementation, and data ingest/egress systems. Work on integrating AI-driven software synthesis into mission-critical database infrastructure that enables seamless platform migrations for enterprise customers.
- Cross-Functional Collaboration and Customer Enablement: Partner with product managers, solution architects, and field engineering teams to understand customer requirements and translate them into technical solutions for complex database migrations. Serve as a technical resource for customers transitioning from legacy platforms to Snowflake, ensuring smooth adoption of AIM Virtualization capabilities.
- Engineering Process Innovation: Define, refine, and improve engineering processes specifically tailored for AI-based software synthesis workflows. Establish best practices for leveraging AI as a high-trust collaborator in development cycles, contributing to standardized methodologies that accelerate development velocity and code quality across the team.
- Database Systems Architecture: Contribute to the architecture and optimization of database virtualization systems, working on query parsing, semantic analysis, and execution optimization. Develop solutions that maintain compatibility with existing SQL dialects and APIs while enabling transparent operation on Snowflake infrastructure.
Qualifications
What we look for.
Technical
SQL Expertise
Advanced proficiency in SQL including query optimization, performance tuning, and complex query design. Must understand SQL dialects, query execution plans, and optimization techniques used across different database platforms for effective virtualization layer development.
Database Internals Knowledge
Solid understanding of database architecture including query parsing, semantic analysis, query optimization algorithms, and execution engines. Experience with database indexing strategies, transaction processing, and optimization for both OLTP and OLAP workloads.
Functional Programming Paradigms
Strong background in functional programming languages and paradigms. Experience with languages such as Scala, Haskell, Lisp, or similar, or demonstrated ability to apply functional programming principles in systems development for building robust, maintainable database systems.
AI/ML Integration in Systems
Demonstrated ability to integrate AI and machine learning models into production systems. Experience with prompt engineering, AI-assisted code generation, or leveraging LLMs for software synthesis to accelerate development cycles and improve system design.
Wire Protocols and Network Programming
Experience with implementing and debugging network protocols, socket programming, and data serialization formats. Understanding of database wire protocols and communication patterns between clients and database servers essential for virtualization layer implementation.
Education
Computer Science Degree
Bachelor's degree in Computer Science, Engineering, or related field required. Advanced degree (MS or PhD) in Computer Science, Databases, High-Performance Computing, or related specialization strongly preferred.
Experience
Backend or Database Systems Engineering
2-7 years of professional experience in backend systems development, database engineering, or distributed systems. Direct experience with SQL-based systems, data warehouses, or analytical platforms highly valued.
Complex Systems Implementation
Demonstrated track record of successfully designing and implementing complex technical solutions. Experience tackling intricate database challenges, building high-performance systems, or working on performance-critical infrastructure.
AI-Native Development Mindset
Experience working in fast-moving, innovation-focused environments with comfort using experimental approaches and emerging AI capabilities. Background leveraging AI as a collaborative tool in development workflows and rapid prototyping.
Skills
Required
SQL and Query Optimization
Expert-level SQL knowledge including complex joins, subqueries, window functions, and query execution plan analysis. Ability to optimize queries for performance and understand how queries execute across different database engines.
Database Architecture and Design
Deep understanding of relational database concepts, indexing strategies, transaction handling, consistency models, and distributed query execution. Knowledge of how data is stored, accessed, and optimized at the storage engine level.
Functional Programming
Proficiency in functional programming languages or strong grasp of functional programming concepts including immutability, higher-order functions, and declarative problem-solving approaches applicable to data transformation systems.
Systems Programming and Low-Level Optimization
Ability to write performant, efficient code with consideration for memory management, CPU cache optimization, and system resource utilization. Experience profiling and debugging complex systems at scale.
AI Integration and Prompt Engineering
Hands-on experience leveraging large language models (LLMs) for code generation, software synthesis, and problem-solving. Understanding of how to effectively communicate technical requirements to AI systems for generating correct, maintainable code.
Preferred
Distributed Systems Experience
Nice to haveExperience designing or maintaining distributed database systems, data warehouses, or cloud infrastructure. Familiarity with challenges in distributed query processing, consistency guarantees, and horizontal scaling.
Snowflake or Competitive Platform Knowledge
Nice to haveHands-on experience with Snowflake, Redshift, BigQuery, or similar cloud-native data platforms. Understanding of modern data stack architecture and integration challenges with legacy systems.
Virtual Machine or Emulation Layers
Nice to haveExperience building virtualization layers, abstraction layers, or compatibility shims between different systems. Prior work on translating or adapting code between different runtime environments or platforms.
Open Source Database Contributions
Nice to haveContributions to open-source database projects such as PostgreSQL, MySQL, or specialized analytical databases. Demonstrated expertise in database systems through public code repositories or published technical work.
Advanced AI Development Techniques
Nice to haveExpertise in advanced AI development methodologies including multi-agent systems, chain-of-thought prompting, or retrieval-augmented generation (RAG). Experience building production AI-augmented development workflows.
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·USD 157,000 – 230,000
Equity·Stock options
Benefits
Equity and Stock Options
Significant stock option packages aligned with Snowflake's public company status, providing substantial upside potential as the company continues to grow in the cloud data platform market.
Comprehensive Health Coverage
Medical, dental, and vision insurance with employer contributions. Mental health support, wellness programs, and preventative care services to support employee wellbeing.
Flexible Work Arrangements
Hybrid or remote work flexibility depending on location and team requirements. Work-life balance initiatives and flexible scheduling to accommodate personal needs.
Professional Development and Learning
Tuition reimbursement programs, conference attendance allowances, and access to technical training resources. Opportunities to work with cutting-edge AI and database technologies with mentorship from industry experts.
Competitive Time Off
Generous paid time off (PTO) policy, parental leave benefits, and sabbatical opportunities. Holidays and wellness days to encourage sustainable work practices.
Retirement Planning
401(k) plans with employer matching contributions. Financial planning resources and retirement counseling to support long-term financial security.
Relocation Assistance
Support for employees relocating to join Snowflake teams, including relocation packages and local area guidance for onboarding new team members.
Process
Interview steps.
- 01
Initial Screening and Technical Assessment
Initial conversation with recruiting team to discuss background, motivation, and alignment with Snowflake culture. Preliminary technical screening to assess SQL proficiency, database knowledge, and AI experience relevant to the role.
- 02
Take-Home Technical Challenge
Hands-on technical assessment involving database system design, SQL query optimization, or AI-assisted development problem. Typically involves designing a virtualization layer component or optimizing complex data transformation logic. Exercise is designed to be completed within 2-4 hours.
- 03
Live Coding Interview - Systems Design
Technical conversation with engineering team member focused on systems design thinking. Discussion of how to architect the virtualization layer, handle API compatibility, optimize query execution, and integrate AI into the development process.
- 04
Database and SQL Deep Dive
Technical interview with database systems expert exploring deep knowledge of query parsing, optimization, execution engines, and how to map queries across different SQL dialects. Scenarios involving complex query transformation and performance analysis.
- 05
AI Integration and Product Context
Discussion with senior engineer about experience leveraging AI in development, prompt engineering approaches, and thoughts on how AI could enhance database systems development. Exploration of candidate's vision for AI-native development processes.
- 06
Product and Cross-Functional Interview
Conversation with product manager or solution architect about understanding customer migration challenges, product direction for AIM Virtualization, and how technical decisions impact customer outcomes and time-to-value.
- 07
Leadership and Culture Fit
Final round with manager or director exploring alignment with Snowflake's values around innovation, experimentation, low-ego collaboration, and thriving in fast-moving environments. Discussion of growth trajectory and career development opportunities.
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.
At Snowflake, we are shaping how data becomes the center piece of the agentic enterprise. Time to value is what’s most critical to our customers. For them, moving from other platforms to Snowflake is key to unlocking new business opportunities and out-innovating their competition.
With AIM Virtualization we’re redefining interoperability for the modern data stack. Our platform makes existing applications instantly work on Snowflake by bringing the core tenets of virtualization to the database. With our runtime, customers move to Snowflake without changing SQL or APIs. As a result, AIM Virtualization makes time-consuming migrations obsolete.
Our platform is uniquely situated at the intersection of database internals and their practical application. Our team gets to tackle some of the most intricate database implementation challenges. All while pioneering an industry-first framework which customers consistently describe as “too good to be true”.
If you’re looking to work on interesting problems that truly matter to our customers while advancing how we can use AI across the organization, this is the team for you. We are looking for AI-first engineers who are not afraid to take on hard and unusual challenges. We are one of Snowflake’s leading teams in AI-driven software synthesis.
Join us if you’re looking to build systems, devise engineering processes, and direct AI systems to synthesize components of a mission critical platform.
Responsibilities:
Participate in AI-based development across the full platform, from syntactic and semantic analysis, to wire protocols, and data ingest/egress.
Collaborate with product managers, solution architects, and field engineering to enable customers make one of the most critical transitions in their database journey.
Define and improve our engineering processes around AI-based software synthesis workflows.
Our ideal candidate will have:
2-7 years of experience in SQL and/or other functional programming languages.
Boundless curiosity and imagination to use AI in novel ways to create a highly robust and scalable data platform.
Solid knowledge of database internals, including query parsing, optimization, and execution.
BS/MS/PhD in Computer Science: databases, high-performance computing, or related fields.
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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