Job Description
Our client is a mid-sized AI startup based in Silicon Valley.
They are looking to hire and upskill Forward Deployed Engineers (FDEs) that will work closely with enterprise customers to design, deploy, and scale cutting-edge agentic AI solutions in complex production environments. This role sits at the intersection of software engineering, solutions architecture, enterprise consulting, product thinking, and AI implementation.
Previous experience working in AI, or as a Forward Deployed Engineer is NOT required or expected, as this is a relatively new role within the industry. High-potential candidates typically come from deep technical, customer-facing backgrounds where they have designed, coded, and deployed complex enterprise software systems.
Common starting points include:
- Solutions Architect
- Senior Backend Engineer
- Senior Fullstack Engineer
- Solutions Engineer
- Platform Engineer
- Cloud Engineer
- DevOps Engineer
- Technical Consultant
- Site Reliability Engineer (SRE)
- Technical Account Manager
Unlike traditional implementation roles, this position requires someone who is equally comfortable leading architecture discussions with customers, writing production-quality code, rapidly prototyping new capabilities, troubleshooting live production systems, and influencing future product direction.
You must be able to articulate your strengths and where your skill gaps are, for the purposes of training. We will be cautious of candidates that oversell their expertise.
Strong professional working fluency in English is REQUIRED. Other Asian languages will be a bonus.
This role is stationed in Ho Chi Minh City, Vietnam but open to candidates applying from all countries as long as they are qualified and able to be deployed in Asia Compensation will scale according to aptitude and experience rather than local market standards alone.
KEY RESPONSIBILITIES:
Partner directly and onsite with enterprise customers to understand their business processes, operational challenges, and existing technology landscape.
Lead technical discovery workshops to understand customer workflows, identify automation opportunities, and define scalable solution architectures.
Analyze complex business processes and redesign them into AI-powered workflows using autonomous agents, orchestration systems, APIs, and enterprise integrations.
Translate ambiguous customer requirements into robust technical architectures that balance customer-specific needs with scalable product design principles.
Own customer implementations end-to-end, including solution design, software development, deployment, production rollout, optimization, and ongoing technical success.
Develop production-quality software to build integrations, extend platform capabilities, automate workflows, and solve complex customer problems.
Build integrations with enterprise platforms such as CRM, ERP, HRIS, identity providers, ticketing systems, collaboration tools, databases, and internal business applications.
Work directly with customer engineering teams to integrate AI solutions into existing cloud infrastructure, APIs, and production software environments.
Rapidly prototype new features, integrations, and proof-of-concepts, often delivering functional solutions within days to validate customer use cases.
Troubleshoot production incidents, integration failures, performance bottlenecks, API issues, and deployment challenges across complex distributed systems.
Collaborate closely with Product and Engineering teams by translating customer feedback into scalable product improvements rather than one-off customizations.
Design reusable implementation patterns, reference architectures, and deployment best practices that can be leveraged across multiple enterprise customers.
Support customer architecture reviews, technical workshops, solution demonstrations, executive presentations, and implementation planning sessions.
Produce high-quality technical documentation, implementation guides, architecture diagrams, API documentation, and deployment playbooks.
Continuously evaluate emerging AI technologies, orchestration frameworks, developer tools, and infrastructure capabilities to improve customer outcomes.
REQUIREMENTS:
At least 5 - 8 years of progressive experience in one or more of the technical roles listed above, working with enterprise software and customers. You MUST have production-grade coding experience; the other skills are more likely to be trainable.- Exceptional interpersonal and communication skills in English, including technical subjects.
- Previous track record of designing, building, and/or deploying enterprise software solutions into production environments.
- Expert in relevant programming languages such as Python and Typescript.
Deep understanding of software architecture, databases, authentication, networking, caching, concurrency, and cloud-native application design.
Prior experience with cloud platforms such as AWS and GCP.- Prior experience deploying applications using Docker, Kubernetes, CI/CD pipelines, Infrastructure-as-Code, and modern DevOps practices.
Prior experience integrating with enterprise software platforms such as Salesforce, SAP, Workday, ServiceNow, Jira, Zendesk, Snowflake, Databricks, Slack, MS Teams, Google Workspace, and others.
Ability to troubleshoot production systems across multiple technology stacks.
Sharp and discerning mindset; able to quickly decipher unfamiliar codebases, enterprise architectures, customer workflows, and technical ecosystems.
Ability to operate in a highly ambiguous environment where customer requirements, product capabilities, and technical constraints evolve rapidly.- Comfortable with a high degree of travel for prolonged periods during deployments.
- Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related technical discipline.
PREFERRED QUALIFICATIONS:
Experience building and/or deploying production AI applications using LLMs.
Experience integrating AI functionality into enterprise software, business workflows, and internal tools.
Familiarity with Retrieval-Augmented Generation (RAG), embeddings, vector databases, tool calling, function calling, prompt engineering, AI evaluation, and agent orchestration concepts.
- Knowledge of agent frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, LlamaIndex, LangChain, and others.
Consulting background, or customer-facing implementation experience involving enterprise software deployments.
If you are qualified and interested, we kindly invite you to apply! In the meantime, please consider following our company page for more updates and relevant job opportunities.
