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Forward Deployed Engineer, Frontier GenAI

San Francisco

SpringCube

Full-time - Senior Engineer

IT Services & Consulting

Posted 22 hours ago

Disclosed upon interview

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview

A leading global professional services organization is expanding its AI & Engineering practice to help enterprises accelerate AI adoption and digital transformation. The team builds, deploys, and operates cutting-edge AI, software, data, networking, and hybrid cloud solutions that modernize mission-critical business operations. Through collaborative, client-focused delivery models, the organization enables businesses to leverage the latest advancements in Generative AI while driving measurable business outcomes across industries.

The organization is seeking a Forward Deployed Engineer, Frontier GenAI to work directly with enterprise clients, transforming AI concepts into production-ready solutions. This role combines software engineering, AI solution development, and client engagement to rapidly prototype, build, and deploy high-impact Generative AI applications.

Key Responsibilities

  • Partner directly with clients to identify business needs and translate high-value Generative AI use cases into scalable solutions.
  • Collaborate with business leaders, product owners, architects, and engineering teams to align project priorities and successful delivery.
  • Lead solution workshops and technical sessions to define AI implementation strategies.
  • Rapidly prototype and deliver production-ready AI applications using modern Generative AI technologies.
  • Contribute independently within cross-functional engineering teams while mentoring junior engineers.
  • Develop AI-enabled applications, agentic workflows, and enterprise AI platforms.
  • Design scalable engineering patterns, human-in-the-loop workflows, and AI tool integrations.
  • Apply architectural best practices that balance quality, security, latency, operational cost, and model risk.
  • Deliver high-quality, maintainable, and well-tested software following modern engineering practices, including CI/CD, version control, logging, testing, and documentation.
  • Build reusable code libraries, prompt libraries, reference implementations, and operational runbooks.
  • Support sprint planning, solution design, and technical decision-making throughout project delivery.

Required Qualifications

  • Bachelor’s degree (or equivalent) in Computer Science, Data Science, Engineering, or a related technical discipline.
  • 3+ years of experience in software engineering, data engineering, data science, or analytics engineering.
  • 1+ year of hands-on experience building and deploying Generative AI or LLM-powered solutions in production or client environments.
  • Experience with one or more leading Frontier GenAI platforms, including Anthropic, Google, or OpenAI technologies such as Claude API, Claude for Enterprise, Gemini API, Vertex AI Agent Builder, GPT-4o, Assistants API, Responses API, or OpenAI Agents SDK.
  • 1+ year of experience leading project workstreams and translating business challenges into AI-powered solutions.
  • Experience developing reliable, maintainable, and well-documented production software.
  • Strong communication and stakeholder management skills with the ability to collaborate directly with enterprise clients.
  • Willingness to travel approximately 50% based on project and client requirements.
  • Eligibility to work within applicable employment authorization requirements.

Preferred Qualifications

  • Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
  • Proven experience working alongside client engineering teams in fast-paced consulting or delivery environments.
  • Background in data engineering using technologies such as Spark, Airflow, dbt, streaming platforms, or machine learning pipelines.
  • Experience with MLOps or LLMOps, including evaluation frameworks, prompt management, and model monitoring.
  • Experience integrating LLM solutions with enterprise systems through APIs, microservices, or event-driven architectures.
  • Experience working within hybrid onshore and offshore delivery teams.
  • Understanding of enterprise security, privacy, governance, and compliance best practices for AI solutions.

Disclaimer

SpringCube curates tech job listings from various company websites to support tech professionals globally.

  1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
  2. No Client Relationship: This company is not a client of SpringCube unless stated.
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