Forward Deployed Engineer – Snowflake

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Company Overview

A leading global professional services organization helps enterprises accelerate innovation through advanced AI, data, cloud, and engineering solutions. By combining deep industry expertise with cutting-edge technology capabilities, the organization enables clients to transform business operations, modernize technology platforms, and drive measurable outcomes through enterprise-scale AI adoption.

The organization is seeking a Forward Deployed Engineer – Snowflake to work directly with clients in designing, prototyping, and deploying high-impact Generative AI solutions. This role sits at the intersection of engineering, product development, client engagement, and AI transformation, requiring a hands-on practitioner who can rapidly deliver business value through innovative technology solutions.

The successful candidate will collaborate with senior client stakeholders, product owners, architects, and engineering teams to build scalable AI-enabled applications and platforms. This position offers the opportunity to drive enterprise AI adoption while developing production-ready solutions using modern AI technologies and Snowflake’s AI ecosystem.

Key Responsibilities

Client Engagement

• Partner with clients to identify business needs and translate high-value Generative AI use cases into practical solutions.
• Collaborate with business leaders, product owners, architects, and engineers to align priorities and delivery objectives.
• Facilitate working sessions to define solution approaches and drive successful client outcomes.
• Prototype and deliver AI-powered solutions leveraging industry knowledge and emerging technologies.
• Contribute independently within engineering delivery teams while mentoring junior team members.

Solution Engineering

• Build AI-enabled applications, agentic platforms, and workflow solutions across enterprise AI ecosystems.
• Develop scalable AI engineering patterns, tool integration approaches, and human-in-the-loop controls.
• Apply architecture decisions that balance performance, quality, security, latency, cost, and model risk.
• Deliver production-quality code following best practices in testing, CI/CD, logging, version control, and documentation.
• Design extensible functionality and contribute to sprint planning and solution delivery efforts.
• Create reusable assets such as 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 building and deploying Generative AI or LLM-powered solutions in production or client environments.
• 1+ years of experience with Snowflake, including hands-on experience with one or more of the following platforms:
  • 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 developing reliable, maintainable, and well-documented code.
• Ability to travel up to 50% based on client and project requirements.
• Eligibility to work within applicable employment requirements.

Preferred Qualifications

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

Disclaimer

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