Objectives
PMAX is building an AI agent capability across the company. Teams are writing decision playbooks, testing them through structured feedback loops, and turning them into repeatable, improvable tools. The first wave of agents is being built now using chatbots and spreadsheets. Your job is to build the infrastructure that takes these proven agents from manual copy-paste to reliable, deployed systems. You will be the first dedicated AI engineering hire. For the first 6–12 months, you are a team of one working closely with the CTO and domain builders across the company. You will not be building agents yourself—domain experts own the logic and the playbooks. You build the rails they run on: the APIs, the UIs, the auth, the logging, the deployment pipeline. When a team has a proven agent that needs to scale beyond copy-paste, you make that happen. This is a building role, not a research role. You will ship working systems, not write papers or train models.
Job Description
- Take proven agents to production. When a team has built and tested an AI agent manually and it's ready for wider use, you build the system around it: API layer, simple UI, auth, deployment. You assess whether existing prototypes can be hardened or should be rebuilt from the documented playbook and decision rules.
- Build workflow automation. Wire LLM APIs to data sources (Google Sheets API, REST endpoints). Build orchestration: scheduled runs, trigger-based execution, output routing. Add proper error handling, retry logic, and fallback behaviour so agents run reliably without manual intervention.
- Set up and own the infrastructure layer. Deployment pipeline (Vercel or similar). Auth layer (Cloudflare Access with company SSO). Logging that captures inputs, outputs, user actions, and override reasons. Environment variable management. Reusable project templates.
- Instrument everything. Every agent run must be auditable: what went in, what came out, which version of the decision framework was used, what the user did with the output. This logging is the company's primary learning signal. Build it well.
- Build protected interfaces for sensitive agents. Some agents contain commercially sensitive decision logic (pricing, margins, competitive positioning). Build interfaces where users can interact with the agent and get results without seeing the underlying framework.
- Own security standards for AI tooling. Review deployments built by non-engineers across the company. Ensure keys aren't hardcoded, SSO is configured, data access is controlled. This is not glamorous. It is essential.
- Support and mentor builders. As more people across the company build AI tools (including with AI-assisted coding), you become the person who reviews their work, helps with architecture decisions, and ensures quality and security standards are met.
Job Requirements
- LLM API integration (non-negotiable). You have built and shipped at least one application that calls an LLM API (OpenAI, Anthropic, Google) in a real-use context—not a hackathon demo. You understand prompt management, token economics, streaming, error handling, and retry logic. You know what a system prompt is and why it matters.
- Full-stack web development. TypeScript/Node.js or Python, ideally both. You can build a functional UI (Next.js or similar), wire up an API layer, and deploy it. You don't need to be a frontend specialist—clean and functional beats pretty.
- Deployment and auth. You have deployed applications to Vercel, Railway, Render, or similar. You can configure SSO (Cloudflare Access or equivalent). You manage secrets properly (.env, platform environment variables, not hardcoded).
- Data integration. You can read from and write to Google Sheets API, REST APIs, and simple databases (Postgres, SQLite). You understand data contracts: schema definitions, column naming conventions, source-of-truth discipline.
- 3–5 years of professional software development experience. You have shipped and maintained software in a team. You understand version control, code review, and why logging matters. You have been on-call or owned a system in production.
Strongly Preferred
- Experience building internal tools or B2B products. You've been close to the business problem, not just executing tickets. You understand that the domain expert knows things you don't, and you build for them, not around them.
- Experience working as a solo engineer or in a very small team. You are comfortable making architecture decisions, setting up infrastructure from scratch, and owning things end to end without a tech lead telling you what to do.
- Monitoring and observability. You have set up logging, structured audit trails, or basic dashboards. You think about what happens after deployment, not just before it.
- Familiarity with Google Workspace ecosystem. Google Sheets API, Google Docs API, Apps Script. Much of PMAX's data lives in Google Workspace. Being comfortable in this ecosystem makes you productive faster.
PMAX-er Identification
- Client Impact: Everything we do is ultimately to deliver real client impact and value.
- Innovation: Drive change and innovative new ideas to create more values for clients, teams and society.
- People Development: Attract, develop, and retain the most talented people. Development is a responsibility, not a choice, of both the individual as well as the organization.
- Integrity: Be honest and show a consistent and uncompromising adherence to what is right, even if it is at our own cost.
- Teamwork & Fun: The cooperative and collaborative effort of a team to achieve a common goal or to complete a task, and trying to build a joyful and enjoyable atmosphere for everyone.
- Extreme Ownership: The practice of owning everything in your world, to an extreme degree. Think of yourself as the owner of the company. It means you are responsible for not just those tasks which you directly control, but for all those that affect whether or not your task is successful.
Benefits
What We Offer
- The chance to build AI infrastructure from scratch at a company that is serious about it—with a governance framework, a training programme, and leadership commitment already in place.
- Direct partnership with the CTO. You are not buried in a large engineering team—you are the engineering team for this initiative, with a direct line to decision-makers.
- Domain exposure across the entire business. You will work with every function: growth, delivery, finance, HR, strategy. Few engineering roles give you this breadth.
- A company that understands that the playbook matters more than the code. You will work with people who have deep domain expertise and respect for what engineering brings to the table.
- Competitive compensation for the Ho Chi Minh City market, with flexibility on remote/hybrid arrangement.
Company Benefits
Competitive salary with quarterly and annual bonuses, and a 13th-month salary Flexible working hours with 4 remote working days per month and 15 annual leave days Comprehensive salary-based insurance (SHUI) Annual regular health check-ups and PTI health care insurance for all employees Providing/laptop allowance or supporting laptop purchase costs for individuals Internal training and career development opportunities, and sponsorship for external L&D budgets Quarterly team bonding budgets, snack time for team bonding Gifts & Awards for Quarters, Years, and special occasions (birthdays, New Year, etc.) Holiday activities; Company trips; Year-end parties; Company birthday; Cultural Day; Quarterly town halls Other welfare benefits for employees.
Job Summary
Year of Experience:
3 years+
Job Level
Middle
Report Line
CTO / Platform Head
Peer
Board of Management (BoM)
Subordinate
None
Salary Range
Negotiable
Hiring Purpose
New Hire
Working Location:
7th Floor, Tuong Viet Building 95 Cach Mang Thang 8, Dist. 1, Ho Chi Minh City, Vietnam
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