Forward Deployed Engineer

We Love AI Jobs; Singapore; Hybrid; SGD 120,000 - 180,000; Full time

Job summary

Zendesk Singapore seeks a Forward Deployed Engineer to design, build, and deploy production-grade AI solutions for strategic customers. You will embed with customers, architect LLM-powered workflows, and surface high-value signals into Zendesk AI deployments.

You will collaborate with Sales engineering and product teams, translate deployments into actionable product feedback, and travel as needed to customer sites while delivering measurable ROI with hybrid work options.

Qualifications

• 5+ years building production AI/ML systems.
• Experience delivering end-to-end AI agent solutions.
• Strong ability to design scalable integrations and data pipelines.

Responsibilities

• Lead end-to-end technical delivery of AI agent and LLM-powered solutions: discovery, scoping, design, PoC, production rollout, handoff.
• Build production-grade integrations and custom connectors (APIs, data pipelines, RAG systems) into Zendesk AI workflows.
• Troubleshoot escalated blockers across data, infrastructure, and model behavior; act as the field's final defense for complex issues.
• Collaborate with Sales engineering and product teams to map undocumented systems and implement patterns.
• Translate customer learnings into product feedback and prioritize roadmap items.

Skills

Python

JavaScript/TypeScript

React

REST/GraphQL APIs

RAG

AWS/GCP/Azure

Docker

Kubernetes

Tools

LangChain

LlamaIndex

Haystack

Job description

# Forward Deployed EngineerZendeskSingapore, SingaporeFull-timeAI tools:LangChainLlamaIndexHaystackUpload your resume once and Scout applies for youApply with ScoutShare this job:LinkedInXSave imageThe Forward Deployed Engineer delivers production AI solutions for Zendesk’s strategic customers, from discovery and system design through deployment and handoff. You’ll build integrations and LLM-powered workflows, resolve complex technical issues, and relay customer learnings to Product and Engineering.* Permanent* Hybrid* 5+ years### Skills and expertisePythonJavaScript/TypeScriptReactREST/GraphQL APIsRAGAWS/GCP/AzureDockerKubernetes### Key responsibilities* Lead delivery of AI agent and LLM solutions from discovery and design through production rollout.* Build integrations, data pipelines, and RAG systems for Zendesk AI workflows.* Troubleshoot complex issues and turn customer deployment learnings into product feedback.## How this job comparesCompared with 1,635 open senior engineering jobs on October 10, 2026.Similar open jobs: We Love AI Jobs lists 1,635 open senior engineering jobs at 344 companies.Remote work: This job is hybrid. 271 of the 1,635 senior engineering jobs (17%) are remote.AI in this role: High. AI is the core of the work: building, training or deploying AI systems. The role is centered on designing, building, and deploying production AI agents and LLM-powered workflows for customers. It also involves RAG, model evaluation, and AI reliability work.## Full descriptionJob DescriptionForward Deployed Engineer (FDE) — AI & SolutionsJoin us at Zendesk, where we're on a mission to power exceptional service for every person on the planet. We're accelerating that ambition by building products rooted in AI, automation, and intelligent customer experiences, because behind every interaction lies an opportunity to make a human connection.We’re hiring a Forward Deployed Engineer (FDE) to join our Technical Presales team. Where you’ll be an elite hybrid: part software engineer, part strategic consultant. You’ll do more than just sell the dream, you’ll execute what’s possible.In this role you’ll be embedded with strategic customers to design, build, and deliver production-grade AI solutions that unlock measurable ROI. You’ll translate customer needs into robust integrations, architect LLM-powered workflows, and collaborate cross-functionally to turn real-world friction into product improvements.You will play a vital role in growing Zendesk’s enterprise footprint by delivering high-impact, scalable AI deployments. Building trusted technical partnerships, delivering crisp, production-ready solutions, and amplifying Zendesk’s AI capabilities within complex, high-value accounts.What you’ll be doing• Lead end-to-end technical delivery of AI agent and LLM-powered solutions: discovery, scoping, system design, PoC, production rollout, and operational handoff.• Build production-grade integrations and custom connectors (APIs, data pipelines, RAG systems) to surface high-quality signals into Zendesk AI workflows.• Troubleshoot and resolve escalated technical blockers across data, infra, and model behavior. Act as the field’s final line of defense for complex issues.• Collaborate closely with Sales engineering and product teams to map undocumented systems, define integration patterns, and implement solutions.• Translate customer learnings into product feedback and prioritized roadmap items; partner with Zendesk Product and Engineering to reduce future deployment friction.What you bring to the role• Founder mindset: comfortable navigating ambiguity, mapping unknown systems, and delivering results without a predefined playbook.• Engineering rigor: 5+ years building production systems; strong software engineering fundamentals and attention to quality.• Full-stack fluency: experience across frontend (React/TypeScript), backend (Python / Node / Java / Ruby), REST/GraphQL APIs, and cloud infrastructure (AWS, GCP, or Azure).• AI/LLM expertise: practical experience with LLMs, prompt engineering, retrieval-augmented generation (RAG), vector stores, and evaluation/guardrails for model safety and reliability.• Systems integrator: proven ability to design secure data ingestion, ETL/data pipelines, and work with diverse data stores and message systems.• Excellent communicator: able to present trade-offs to executives and pair-program with customer engineers; strong written runbooks and documentation skills.• Travel readiness: willing to travel as needed to customer sites (typical range 25–50%).Basic qualifications• 5+ years software engineering experience delivering production systems.• Proficient in Python and JavaScript/TypeScript; experience with at least one backend language (Java, Ruby, or Go) preferred.• Hands-on experience deploying or integrating LLM-based solutions in production (RAG, vector DBs, model evaluation).• Practical experience with cloud platforms (AWS/GCP/Azure) and containerized deployments (Docker, Kubernetes).• Comfortable working onsite with customers and traveling up to 50% as required.