Forward Deployed Engineer – Snowflake

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Company Overview

A leading global professional services organization is seeking a Forward Deployed Engineer – Snowflake to help enterprise clients accelerate AI adoption and deliver measurable business outcomes. This role focuses on building and deploying Generative AI solutions, collaborating directly with clients, and leveraging modern AI engineering practices to develop scalable, production-ready applications. The position offers the opportunity to work on high-impact AI transformation initiatives across various industries while partnering with cross-functional engineering and business teams.

The organization is seeking a Forward Deployed Engineer – Snowflake to design, prototype, and deliver enterprise-scale AI solutions that solve complex business challenges. This role requires a hands-on engineering professional who thrives in fast-paced environments, works closely with senior client stakeholders, and transforms AI concepts into production-ready solutions.

The successful candidate will collaborate with technical and business teams to develop AI-powered applications, implement scalable engineering practices, and contribute reusable assets that support long-term client success. This position also requires balancing solution quality, performance, security, and maintainability while driving innovation in enterprise AI deployments.

Key Responsibilities

• Collaborate directly with clients to identify business challenges and translate high-value Generative AI use cases into technical solutions.
• Partner with product owners, architects, engineering teams, and business leaders to align project priorities and execution.
• Lead discovery workshops and working sessions to define solution strategies and deliver measurable client outcomes.
• Prototype, develop, and deploy AI-powered applications using modern enterprise AI platforms.
• Contribute independently within cross-functional engineering teams while mentoring junior engineers.
• Design and develop AI-enabled applications, agentic workflows, and enterprise AI platforms.
• Implement scalable AI engineering patterns, workflow orchestration, and human-in-the-loop controls.
• Make architectural decisions that balance performance, security, quality, latency, cost, and model risk.
• Deliver production-quality software using industry best practices, including testing, CI/CD, version control, logging, monitoring, and documentation.
• Design extensible application components and contribute to sprint planning and technical estimations.
• Develop reusable engineering assets, including code libraries, prompt libraries, runbooks, and reference implementations.

Required Qualifications

• Bachelor’s degree (or equivalent) in Computer Science, Data Science, Engineering, or a related field.
• 3+ years of experience in software engineering, data engineering, data science, or analytics engineering.
• 1+ years of hands-on experience developing and deploying Generative AI or LLM-powered solutions in production or client environments.
• 1+ years of experience with Snowflake, including hands-on expertise with one or more of the following:
  • Cortex AI
  • Cortex LLM Functions
  • Cortex Agents
  • Arctic Embed
• 1+ years of experience leading project workstreams and translating business requirements into AI solutions.
• 1+ years of experience building reliable, maintainable, and well-documented software.
• Ability to travel approximately 50%, depending on project and client requirements.
• Limited immigration sponsorship may be available.

Preferred Qualifications

• Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
• Experience working directly with client technical teams and program stakeholders in fast-paced delivery environments.
• Background in data engineering using Spark, Airflow, dbt, streaming technologies, data modeling, or machine learning.
• Experience with MLOps or LLMOps practices, including evaluation frameworks, model monitoring, and prompt management.
• Experience integrating LLM solutions with enterprise systems through APIs, microservices, or event-driven architectures.
• Experience collaborating within hybrid onshore and offshore engineering teams.
• Familiarity with enterprise security, privacy, governance, and compliance requirements.

Disclaimer

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