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About This Role
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.
Staff Software Engineer – File Ingestion (Customer-Facing Services)
Build the Future of the AI Data Cloud
Snowflake’s File Ingestion team owns the core engines behind COPY INTO and Snowpipe — the primary arteries landing customer data into the AI Data Cloud at hundreds of petabytes per quarter.
We are expanding our core mission to build next-generation, external-facing ingestion services that directly expose file-ingest capabilities to external platforms, partner ecosystems, and customer applications. As a Staff Software Engineer, you will lead the architectural vision and execution for these mission-critical, customer-facing services. You will operate at the intersection of high-throughput distributed systems, API platform design, and direct customer feature delivery, defining how enterprise data seamlessly flows into Snowflake at global scale.
What You’ll Do
- Drive Technical Vision & Architecture: Define the multi-year architecture and technical strategy for high-throughput, external-facing ingestion services and APIs across multi-cloud environments (AWS, Azure, GCP).
- Deliver Customer-Facing Innovations: Lead the end-to-end execution of enterprise-grade external features, ensuring low-latency data landing, high availability, and seamless ecosystem integration (e.g., Snowpark Connect, partner connectors).
- Set Technical Direction: Author foundational design documents, establish technical standards for reliability, security, and scalability, and lead high-stakes architectural reviews across engineering orgs.
- Lead Cross-Functional Alignment: Partner closely with Principal Architects, Product Management, Security, and external developer platforms to translate customer requirements into resilient system architecture.
- Elevate Engineering Excellence: Mentor and sponsor Senior, Mid-level, and Junior engineers; raise the bar for system design, code quality, testing methodologies, and operational maturity.
- Direct Customer & Strategic Impact: Engage with enterprise customer engineering teams to solve complex integration challenges, debug production edge cases at scale, and turn direct customer feedback into core platform capabilities.
What We’re Looking For
- 10+ years of experience designing, building, and operating large-scale distributed systems or cloud-native infrastructure in production.
- Proven track record of architectural leadership, having successfully taken complex, customer-facing services or external APIs from initial concept to General Availability (GA) and global scale.
- Expert proficiency in Java or C++ (strong preference for engineers comfortable working across both systems-level C++ and managed service Java frameworks).
- Deep expertise in external API design, cloud service orchestration, and building resilient, multi-tenant customer-facing endpoints.
- Deep domain knowledge in at least one of the following: high-throughput ingestion pipelines, distributed query execution engines, messaging/streaming systems (e.g., Kafka, Pulsar), or database internals.
- Exceptional written and verbal communication skills with a demonstrated ability to drive technical consensus across cross-functional leadership, product partners, and external technical stakeholders.
- BS, MS, or PhD in Computer Science, Computer Engineering, or equivalent practical experience.
Bonus Points
- Experience building and scaling external developer platforms, SDKs, or public SaaS APIs serving external consumers.
- Deep expertise with open table formats (Apache Iceberg, Delta Lake) and integration with ecosystems like Apache Spark or Ray.
- Advanced performance engineering expertise: memory management, SIMD, vectorization, lock-free data structures, or I/O optimization at PB-scale.
- Strong background in metadata management, transactional state machines, or consensus protocols (e.g., Raft, Paxos).
- Active contributor to open-source data infrastructure, cloud-native compute systems, or query engines.
Why This Team
- Massive Strategic Impact: You will lead the expansion of Snowflake's most critical data-path surface into direct, customer-facing integrations that unlock new platform ecosystems and drive platform volume.
- Broad Architectural Scope: Your work will bridge edge API layers, control-plane orchestrators, file scanners/parsers, query planners, and underlying storage engines.
- High Customer Visibility: Work directly on features that power the external integrations for Fortune 500 enterprises, seeing the immediate revenue and performance impact of your architecture.
- Culture of Technical Leadership: Partner directly with Snowflake’s top architects and leads in an environment that values deep technical autonomy, rigorous engineering, and long-term architectural stewardship.
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
The following represents the expected range of compensation for this role:
- The estimated base salary range for this role is $236,000 - $339,200.
- Additionally, this role is eligible to participate in Snowflake’s bonus and equity plan.
The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending & health savings account; at least 12 paid holidays; paid time off; parental leave; employee assistance program; and other company benefits.
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Salary Context
This $236K-$339K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $192K across 244 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 10,827 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Snowflake, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $220,000 based on 1,689 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($287K) sits 31% above the category median. Disclosed range: $236K to $339K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,111. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,300; VP: $236,450.
Snowflake AI Hiring
Snowflake has 14 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer, AI Product Manager, Data Scientist. Positions span Bellevue, WA, US, Denver, CO, US, Menlo Park, CA. Compensation range: $126K - $339K.
Location Context
Across all AI roles, 6% (665 positions) offer remote work, while 10,097 require on-site attendance. Top AI hiring metros: New York (3,262 roles, $221,000 median); San Francisco (2,767 roles, $260,600 median); Los Angeles (1,585 roles, $210,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 10,827 open positions tracked in our dataset. By seniority: 122 entry-level, 5,256 mid-level, 3,922 senior, and 1,527 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (665 positions). The remaining 10,097 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,111. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 10,827 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,288), AI Software Engineer (548), AI Product Manager (471). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (122) are outnumbered by mid-level (5,256) and senior (3,922) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,527 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (665 positions), with 10,097 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,111, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,093 postings), Aws (1,100 postings), Azure (910 postings), Rag (863 postings), Gcp (680 postings), Pytorch (549 postings), Claude (532 postings), Kubernetes (511 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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