Forward Deployed Engineer

Apple Inc

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Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $216,200–$324,800 / yr
Posted: 132 days ago
Freshness: Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $185k

This role $270k

$121k $347k

below market most similar roles pay here above market

This role pays more than 95% of similar roles. Most pay $147,182–$222,500 — the blue band above. At the midpoint, this role pays about $270k versus about $185k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

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At a glance

TL;DR · Forward Deployed Engineer

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The Forward Deployed Engineer joins the US Decision Intelligence team to bridge the gap between Sales and engineering. This role involves embedding with Sales teams to translate ambiguous business problems into shippable code and engineering specifications. You will build prototypes, demos, and reference implementations that solve concrete Sales problems, eventually distilling these into reusable platform features. Key responsibilities include operationalizing novel models with data science teams and integrating solutions with platform APIs and SDKs. Required technical skills include proficiency in Python, JavaScript, Node.js, SQL, and relational databases like PostgreSQL or Snowflake. You must possess functional literacy in AI/ML concepts, specifically LLM-powered systems involving prompts, retrieval, and inference. Experience with REST APIs, GraphQL, microservices, Docker, and Kubernetes is also required to support these internal AI-driven insight platforms.

What does a Forward Deployed Engineer earn?

Median $219575 from 46 postings across 19 companies.

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Skills

Python JavaScript Node.js SQL PostgreSQL Snowflake LLM GraphQL REST APIs Microservices Docker Kubernetes Airflow Dataiku React Express.js Langfuse PagerDuty

What you'll do

Translate ambiguous business problems from Sales teams into technical engineering specifications and shippable solutions.
Build prototypes, demos, and reference implementations to solve immediate sales problems using the internal AI platform.
Convert successful prototype patterns into reusable code and first-class features for the core product roadmap.
Partner with data science teams to operationalize models and scoring algorithms into production-grade services.
Integrate sales-facing solutions with platform APIs, SDKs, and shared services to enable self-service adoption.
Provide structured feedback on API quality and developer experience to inform Product Management's prioritization.
Create tutorials, onboarding materials, and documentation to build an internal community around the platform.
Communicate technical trade-offs and project outcomes clearly to stakeholders across the entire development lifecycle.

What we're looking for

8+ years of experience in Forward Deployed Engineering, Solutions Architecture, full-stack product engineering, or a related technical role.
Ability to translate ambiguous business requirements into concrete engineering specifications and prototypes.
Proficiency in Python and JavaScript/Node.js for end-to-end full-stack development.
Familiarity with SQL, relational databases like PostgreSQL or Snowflake, and data pipelines.
Functional literacy in AI/ML concepts including LLM systems, prompts, retrieval, evaluation, and inference.
Experience partnering with data scientists to operationalize prototype code into production-grade services.
Working knowledge of REST APIs, GraphQL, microservices, and distributed systems architectures.
B.S. degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience.
Experience supporting Sales, Operations, and Finance stakeholders (preferred).
Hands-on experience building LLM-powered applications and prompt design (preferred).
Familiarity with data science tools like Dataiku, Snowflake, Airflow, or Docker/Kubernetes (preferred).
Advanced Degree (MS) in Computer Science, Engineering, Data Science, or a related field (preferred).

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