Principal Forward Deployed Engineer II, Frontier Engineering

Principal Engineer · Principal · Full Time

US-CA-Menlo ParkUSD 304k – 437k2w ago
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Role

What you'll do.

Principal Forward Deployed Engineer II (IC6) at Snowflake's Frontier Engineering team, responsible for serving as senior technical authority and architectural leader for high-impact customer AI deployments. This role involves designing, building, and deploying production-grade AI systems at enterprise scale while influencing product direction and mentoring senior technical talent across strategic customer engagements.

Responsibilities

  • Serve as Senior Technical Authority and Architectural Leader: Build peer-level relationships with CTOs, VPs of Engineering, chief architects, and heads of data and AI at Snowflake's most strategic accounts. Lead architectural steering, technical reviews, and executive strategy alignment while shaping multi-year AI roadmaps across a portfolio of customer engagements and demonstrating executive presence in high-stakes technical discussions.
  • Drive Architecture and Technical Strategy Across Portfolio: Own end-to-end outcomes for multiple complex, high-visibility AI deployments. Set technical strategy and execution models, arbitrate difficult cross-system tradeoffs, and establish replicable patterns that scale across customers, teams, and business units while managing risk in enterprise-grade production systems.
  • Influence Snowflake Product Direction: Translate recurring customer needs and production deployment learnings into clear, prioritized product requirements. Partner with Product and Engineering leadership to drive adoption of new capabilities and ensure field learnings directly improve platform features and customer outcomes at scale.
  • Maintain Hands-On Technical Leadership: Write production-grade code and working prototypes on the most critical or ambiguous parts of customer programs. Conduct design and code reviews, demonstrate technical depth and judgment expected at the IC6 level, and stay close to implementation details that determine system success.
  • Define AI Quality, Reliability, and Responsible Deployment Standards: Establish organization-level standards for AI system evaluation, observability, reliability, security, guardrails, and responsible deployment. Convert ambiguous customer goals into clear, testable measures and ensure consistent application across all engagements and teams.
  • Provide Technical Leadership and Develop Senior Talent: Mentor Principal, Staff, and Senior engineers while developing technical leads and raising engineering standards across the organization. Lead through influence and informal authority across Engineering, Product, Sales, and cross-functional teams to amplify impact beyond direct reporting.
  • Customer-Embedded On-Site Engagement: Travel to strategic customer sites for at least 25% of the role, working directly with customer engineering teams to understand requirements, validate architectures, troubleshoot production issues, and build trust-based advisory relationships that extend across multiple years.

Qualifications

What we look for.

Technical

  • Production AI/ML Systems Architecture

    15+ years of software engineering experience with sustained track record building and shipping production-grade AI and machine learning systems at enterprise scale, including agentic architectures and AI platform deployments.

  • Retrieval-Augmented Generation (RAG) Pipelines

    Deep expertise in designing, implementing, and optimizing RAG pipelines for enterprise applications, including vector databases, retrieval strategies, ranking algorithms, and prompt engineering at scale.

  • Multi-Step Agentic Systems

    Demonstrated expertise building and operating complex agentic systems with multiple reasoning steps, tool integration, planning capabilities, and the reliability patterns required for production enterprise deployments.

  • Evaluation and Observability Frameworks

    Hands-on experience designing evaluation frameworks, observability systems, and monitoring solutions for AI applications, including metrics for accuracy, latency, cost, and user outcomes in production environments.

  • AI Security, Guardrails, and Responsible AI

    Expertise in securing production AI systems, implementing guardrails against misuse, designing responsible AI practices, compliance frameworks, and ensuring enterprise-grade safety in AI deployments.

  • Enterprise Data Infrastructure and Cloud Platforms

    Strong working knowledge of modern cloud data warehousing, data lakes, streaming platforms, and enterprise data infrastructure used to support AI and machine learning workloads at scale.

Education

  • Bachelor's Degree in Computer Science or Related Field

    Formal education in Computer Science, Software Engineering, Mathematics, or related discipline, or equivalent industry experience demonstrating deep technical foundation in software architecture and systems design.

Experience

  • Trusted Technical Advisor to Enterprise Leadership

    Proven track record serving as trusted technical advisor to CTOs and VP-level engineering leaders at large enterprises. Demonstrated ability to set technical direction across multiple strategic accounts or major enterprise programs while influencing executive-level decision-making.

  • Customer-Centric Platform and Tool Development

    Demonstrated success converting client delivery patterns, field learnings, and customer feedback into reusable platforms, tools, frameworks, reference architectures, or open-source libraries that achieve adoption across teams or customer bases.

  • Enterprise AI Solution Delivery and Deployment

    Experience designing, building, and deploying end-to-end AI solutions in complex enterprise environments with multiple stakeholders, legacy systems integration, and the operational challenges of scaling AI in production.

  • Cross-Functional Technical Leadership and Influence

    Track record of leading technical initiatives across organizational boundaries, influencing without formal authority, and aligning multiple teams (Engineering, Product, Sales, Data) around a unified technical strategy.

Skills

Required

  • Advanced Python Programming

    Expert-level proficiency in Python for building production AI systems, data pipelines, and working prototypes. Experience with Python ML frameworks, async programming, and performance optimization for enterprise workloads.

  • Distributed Systems Design

    Deep understanding of distributed systems architecture, consistency models, fault tolerance, and scalability patterns. Ability to design systems that operate reliably across multiple regions and handle enterprise-scale traffic.

  • Large Language Models and Foundation Models

    Hands-on experience working with LLMs, foundation models, and AI platforms. Proficiency in prompt engineering, fine-tuning approaches, model selection trade-offs, and operationalizing models in production.

  • Systems Thinking and Architecture

    Ability to think holistically about complex technical systems, understand interdependencies, design for scalability and reliability, and make well-reasoned architectural tradeoffs between competing requirements.

  • Executive Communication and Influence

    Exceptional ability to communicate complex technical concepts to both deeply technical and executive audiences. Proven skill in influencing decision-making through clear articulation of tradeoffs, risks, and strategic direction.

  • Code Review and Technical Leadership

    Ability to conduct thorough code reviews, provide constructive feedback that raises technical standards, mentor senior engineers, and set the bar for code quality and architectural rigor across teams.

Preferred

  • Cortex AI and Snowflake Platform Expertise

    Nice to have

    Familiarity with Snowflake's Cortex AI, Snowpark, and modern enterprise data infrastructure platforms. Knowledge of how Snowflake integrates with AI workflows and understanding of cloud-native data architecture.

  • Open-Source AI Framework Contributions

    Nice to have

    Active contributions to open-source AI and ML frameworks, libraries, or tools. Demonstrated commitment to the broader developer community through meaningful technical contributions.

  • Technical Publications and Industry Speaking

    Nice to have

    Published technical articles, whitepapers, or conference talks on AI architecture, enterprise ML systems, or agentic systems. Visibility as a thought leader in the AI and machine learning community.

  • Vector Databases and Semantic Search

    Nice to have

    Hands-on experience with vector databases, embedding models, similarity search, and semantic retrieval systems commonly used in modern AI applications and RAG architectures.

  • Cloud Platform Services (AWS, Azure, GCP)

    Nice to have

    Deep experience with cloud provider services for AI and ML workloads, including managed ML services, container orchestration, serverless computing, and cloud-native security patterns.

  • MLOps and Model Operations

    Nice to have

    Experience building MLOps platforms, model serving infrastructure, continuous training pipelines, experiment tracking systems, and operational practices for maintaining AI systems in production.

Tech stack

Languages

PythonSQLTypeScript/JavaScript

Frameworks

LangChainLlamaIndexFastAPIPyTorchHugging Face Transformers

Databases

SnowflakeVector Databases (Pinecone, Weaviate, Milvus)PostgreSQL

Tools

Git and GitHubDocker and KubernetesCloud Platforms (AWS, Azure, GCP)Monitoring and Observability (Datadog, New Relic, Prometheus)Jupyter Notebooks and IDE Tools

Other

Agentic Frameworks and Planning SystemsEvaluation and Testing FrameworksEnterprise Architecture PatternsSecurity and Compliance (OAuth, encryption, GDPR, SOC2)

Compensation

Pay and benefits.

Base·USD 304,000 – 437,000

Equity·Stock options

Benefits

  • Comprehensive Health Insurance

    Medical, dental, and vision coverage for employees and dependents with Snowflake contributing a significant portion of premiums and providing choice of plan options.

  • Competitive Retirement Benefits

    401(k) plan with company matching and investment options to support long-term financial planning and wealth building.

  • Generous Time Off Policy

    Flexible paid time off, holidays, and wellness days to maintain work-life balance and support personal well-being and professional growth.

  • Equity and Stock Options

    Competitive stock option packages as part of total compensation, allowing employees to participate in Snowflake's growth as a public company.

  • Professional Development and Learning

    Access to technical training, conference attendance budgets, and professional development programs to keep skills current with evolving AI and cloud technologies.

  • Relocation and Mobility Support

    Assistance with relocation for qualified candidates and support for frequent travel requirements inherent to customer-embedded engineering roles.

  • Mental Health and Wellness Programs

    Employee assistance programs, mental health resources, wellness initiatives, and fitness benefits to support holistic employee well-being.

  • Parental Leave and Family Support

    Comprehensive parental leave policies, fertility support, and family-friendly benefits reflecting Snowflake's commitment to supporting all life stages.

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.

Snowflake is about empowering enterprises to achieve their full potential, and people too. With a culture that's all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology and careers to the next level.

We are hiring a Principal Forward Deployed Engineer II for our Frontier Engineering team. This team embeds directly with Snowflake's most strategic customers to design, build, and deploy production-grade AI systems . At the IC6 level, you serve as the senior technical authority and architectural leader for a portfolio of high-impact customer engagements. You operate as a peer technical advisor to CTOs, VPs of Engineering, chief architects, and heads of data and AI, setting technical direction that extends beyond individual accounts and influences how Snowflake delivers AI solutions at scale.

AS A PRINCIPAL FORWARD DEPLOYED ENGINEER II YOU WILL:

  • Serve as the senior technical authority and architectural leader for customer engineering leadership: Build durable, peer-level relationships with CTOs, VPs of Engineering, chief architects, and heads of data and AI at Snowflake’s most strategic accounts. Lead architectural steering, technical reviews, and executive strategy alignment while shaping multi-year AI roadmaps across a portfolio of customers.

  • Drive Architecture and Technical Strategy Across a Portfolio of High-Stakes Deployments: Set the technical strategy, architecture, and execution model across multiple complex, high-visibility AI engagements. Own end-to-end outcomes, arbitrate the most difficult cross-system tradeoffs, and establish patterns that scale across customers, teams, and business units.

  • Influence Snowflake Product Direction: Translate recurring customer needs and deployment learnings into clear product requirements, partner with Product and Engineering leaders, and drive adoption of capabilities that improve outcomes across the field.

  • Stay hands-on and set the engineering bar: Write production code and working prototypes on the most critical or ambiguous parts of customer programs, review designs and code, and demonstrate the technical depth and judgment expected across the organization.

  • Set the AI quality and reliability bar: Define organization-level standards for evaluation, observability, reliability, security, guardrails, and responsible deployment. Turn ambiguous customer goals into clear, testable measures and ensure those standards are applied consistently across engagements.

  • Provide technical leadership and develop senior technical talent: Mentor Principal, Staff, and Senior engineers; develop technical leads; raise engineering standards across the organization; and lead through influence across Engineering, Product, Sales, and other cross-functional teams.

  • Travel to Customer Sites: Spend at least 25% of your time onsite working with customers.

OUR IDEAL CANDIDATE WILL HAVE:

  • 15+ years of software engineering experience, including a sustained track record of building and shipping production AI/ML or agentic systems at enterprise scale.

  • Proven track record serving as a trusted technical advisor to CTOs and executive engineering leaders at large enterprises, and setting technical direction across multiple strategic accounts or enterprise programs.

  • Demonstrated success converting client and field delivery patterns into reusable platforms, tools, frameworks, reference architectures, or open-source libraries adopted across teams or customers.

  • Deep expertise in production AI architectures—including RAG pipelines, multi-step agentic systems, evaluation frameworks, guardrails, observability, security, and operating models for enterprise-scale adoption.

  • Hands-on technical leader who writes and reviews production code, stays close to implementation, and can move from executive strategy to the critical technical details that determine whether a system succeeds.

  • Exceptional systems thinking and technical communication skills across deeply technical and executive audiences, with the ability to influence without formal authority and align multiple organizations around a common technical strategy.

BONUS POINTS FOR THE FOLLOWING:

  • Experience leading cross-organizational technical initiatives that improve how enterprise AI solutions are designed, deployed, and adopted.

  • Active contributions to open-source AI frameworks, technical publications, or industry speaking engagements.

  • Familiarity with Cortex AI, Snowpark, or modern enterprise data infrastructure platforms.

WHY JOIN FRONTIER ENGINEERING AT SNOWFLAKE?

Frontier Engineering is where Snowflake’s AI platform meets reality — you’re not building demos, you’re shipping AI applications that run in some of the world’s most complex enterprise environments. At the IC6 level, you also define the reusable architectures, engineering standards, and product feedback loops that allow these solutions to scale across customers. You will work on hard problems with real stakes, alongside engineers who are deeply technical and customer-obsessed.

How do you want to make your impact?

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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