Subscribe
This posting is more than 14 days old. The apply window may have closed — browse all active FDE roles.
Google

Forward Deployed Engineer, Generative AI, Telecommunications, Google Cloud

$153K - $222K New York, NY, US Posted April 06, 2026

Role Description

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Addison, TX, USA; Austin, TX, USA; New York, NY, USA.### Minimum qualifications:

  • Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
  • 6 years of experience in Python and relevant machine learning packages (e.g., Keras, HF Transformers).
  • Experience in applied AI, with a focus on designing and evaluating systems around foundation models (e.g., prompt engineering, fine-tuning, RAG, orchestrating model interactions with external tools to deliver solutions).
  • Experience architecting, deploying, or managing solutions on a cloud platform.

Preferred qualifications:

  • Master’s degree or PhD in AI, Computer Science, or a related technical field.
  • Experience delivering AI solutions specifically for telecommunications use cases, such as network optimization, churn prediction, or customer experience enhancement.
  • Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s ADK) and complex patterns like ReAct, self-reflection, and hierarchical delegation.
  • Knowledge of "LLM-native" metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
  • Ability to implement secure agentic workflows incorporating MCP, tool-calling, and OAuth-based authentication.

About the job -----------------

As a GenAI Forward Deployed Engineer (FDE) at Google Cloud, you are an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you function as a "builder-consultant," moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment.

You will manage blocker to production including solving the integration complexities, data readiness issues, and state-management challenges that prevent AI from reaching enterprise-grade maturity. By embedding with strategic accounts, you serve a dual purpose: providing "white glove" deployment of complex AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.

Your primary responsibility will be to construct rapid prototype Generative AI applications tailored to Google Cloud customers, catering to a clientele ranging from early stage startups to prominent, established companies.

You will be a hybrid professional, blending the core competencies of an engineer with an aptitude for customer engagement and strategic problem-solving. This will often require you to lead with deep, bespoke implementation as the primary value proposition, ensuring that our core technology delivers demonstrable value in the customer's unique operational context.

You will have close collaboration with our product and engineering teams to eliminate obstacles and shape the future trajectory of our offerings. You will be adept at disseminating lessons learned to customers and internal Google teams, translating one-off customer solutions into reusable, scalable assets.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $153,000-$222,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities --------------------

* Serve as the lead developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable ROI. * Architect and code the "connective tissue" between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters. * Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency. * Identify repeatable field patterns and technical "friction points" in Google’s AI stack, converting them into reusable modules or product feature requests for the Engineering teams. * Drive engineering excellence by mentoring talent, co-building with customer teams, and influencing cross-functional strategies to uplevel organizational technical capabilities. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

About Forward Deployed Engineering

Forward Deployed Engineers are embedded directly with customers to build custom solutions, integrate products into existing infrastructure, and bridge the gap between product engineering and customer success. The role combines deep technical skills with the ability to operate in client environments and translate business requirements into working software.

Originally pioneered by Palantir, the FDE model has spread across AI, enterprise SaaS, and cloud infrastructure companies. FDEs write production code, architect integrations, train customer teams, and feed product insights back to the core engineering organization. At companies like OpenAI, Salesforce, and Databricks, FDE teams are treated as elite engineering units that can ship custom solutions in days rather than quarters.

Typical FDE stack: Python, TypeScript, SQL, REST/GraphQL APIs, cloud platforms (AWS/GCP/Azure), and increasingly LLM APIs and AI orchestration frameworks. Strong communication and the ability to context-switch between technical and business conversations are as important as coding ability.

Get the FDE Pulse Brief

Weekly market intelligence for Forward Deployed Engineers. Job trends, salary data, and who's hiring. Free.