Tech Lead, Agentic Engineering

The role

We are looking for a Tech Lead, Agentic Engineering to lead our Vietnam-based engineering team building Growtrics’ next generation of agentic and multi-agent AI systems.

You will be the most senior technical leader in our Vietnam engineering team, working closely with the CTO every day and leading a team of Agentic / Backend Engineers.

This role combines strong technical depth with seasoned engineering management. You should be able to understand and challenge architecture, review complex agentic systems and get into the code when necessary. Your primary responsibility, though, is building a high-performing, efficient and accountable engineering team.

Key responsibilities

• Lead and manage the Vietnam-based Agentic Systems Engineering team as it grows.
• Work closely with the CTO on technical direction, architecture, engineering priorities and major technical decisions.
• Set engineering standards across architecture, code quality, testing, documentation, observability, security and reliability.
• Establish effective engineering cadence, planning, reviews, communication and accountability.
• Break large technical initiatives into clear workstreams, milestones, ownership and deliverables.
• Ensure engineers understand both what they are building and the outcome they are responsible for.
• Review technical approaches and architecture for complex agentic and backend systems.
• Mentor engineers and provide technical and career guidance without becoming a bottleneck.
• Identify technical debt, recurring engineering problems and gaps in team capability, and drive them to resolution.
• Work closely with Product, Design, QA and other teams to turn requirements into executable technical plans.
• Own engineering execution from technical planning through development, testing, deployment and production operation.
• Recruit, evaluate, develop and retain strong engineers as the team grows.
• Build a culture where engineers raise problems early, challenge assumptions, document decisions and own outcomes.
• Continuously evaluate AI engineering tools, agentic coding harnesses and development practices that improve engineering productivity.

Agentic systems engineering

You should have strong technical depth in the systems the team is building, including:

• Agentic and multi-agent LLM systems built primarily with Python
• Agent orchestration, tool calling, state management, memory, retries, evaluation and human-in-the-loop workflows
• Backend systems involving jobs, queues, state machines, asynchronous workflows, validation and failure recovery
• LLM providers such as OpenAI, Claude, Gemini and Perplexity
• Agentic coding harnesses such as Claude Code, Codex, Cursor or equivalent tools
• FastAPI and modern Python backend development
• Firebase and GCP services such as Cloud Run, Firestore, Pub/Sub and Cloud Tasks
• Automated testing and evaluation of AI and agentic systems
• Observability, debugging, reliability and production operations

Examples of systems the team may build:

• Multi-agent systems that autonomously generate and refine educational content
• AI systems for grading, feedback generation, learning-path optimisation and AI-assisted review
• Agents coordinating LLMs, external tools, APIs, databases, queues and human approval steps
• AI-powered QA systems that simulate users, reproduce bugs and identify failures
• Agentic workflows using coding harnesses such as Claude Code or Codex to implement, test, debug and improve software
• Internal AI agents that automate complex business and operational workflows

You are not expected to write every feature yourself. Your responsibility is to make sure the team can build these systems effectively, correctly and repeatedly at scale.

Engineering management and team leadership

This is a critical part of the role. We are looking for someone who has actually run engineering teams, not simply someone who has been the most senior engineer on a team. That means experience with:

• Running effective daily and weekly engineering cadences
• Sprint or milestone planning, execution and delivery tracking
• Technical planning, work breakdown, dependency management and blocker removal
• Code and architecture review processes and engineering quality gates
• Incident management, post-mortems and reliability improvement
• Technical debt and engineering capacity management
• One-to-ones, feedback, coaching and performance management
• Hiring and interviewing engineers
• Delegating effectively while keeping technical visibility
• Handling underperformance and improving team accountability
• Resolving disagreements between Engineering, Product, Design, QA and leadership
• Building autonomous teams without losing alignment or technical discipline

You should understand the language, hygiene, cadence and operating practices of strong engineering teams and technology pods. The goal is not more process or meetings. It is a team that moves quickly, communicates clearly, maintains high standards and reliably delivers.

Soft skills

• Leadership and people management. Proven ability to lead, mentor, develop and hold engineers accountable.
• Technical judgement. Able to understand complex problems, challenge assumptions, make trade-offs and know when to go deep or delegate.
• Ownership. Takes responsibility for team outcomes rather than only personally assigned tasks.
• Communication. Clear English communication with engineers, Product, the CTO, leadership and non-technical stakeholders.
• Execution. Turns ambiguous technical goals into clear plans, milestones, ownership and outcomes.
• Coaching. Develops engineers into stronger independent problem-solvers.
• Systems thinking. Understands the relationship between architecture, people, process, product and business outcomes.
• Result oriented. Assessed on the quality, reliability and timeliness of team output.
• Continuous learning. Comfortable learning rapidly in a fast-changing AI engineering environment.

Technical skills

• Strong hands-on experience building agentic and multi-agent LLM systems in Python
• Strong backend architecture and distributed systems fundamentals
• Strong proficiency with FastAPI and modern Python backend development
• Experience with Firebase and GCP, including Cloud Run, Firestore, Pub/Sub, Cloud Tasks or similar services
• Strong understanding of APIs, asynchronous jobs, queues, state machines, retries, validation and failure handling
• Experience with multiple LLM providers such as OpenAI, Claude, Gemini and Perplexity
• Experience with agent orchestration, tool calling, memory, evaluation loops and human-in-the-loop systems
• Familiarity with agentic coding harnesses such as Claude Code, Codex, Cursor or equivalent
• A strong testing, documentation, observability, debugging and production reliability mindset
• Experience using LLMs or agents to simulate user behaviour, generate tests, detect bugs and reproduce failures
• Experience with CI/CD, monitoring, alerting, deployment and production operations

Experience with the following is preferred:

• Vector databases such as Qdrant, Weaviate or Milvus
• Graph databases such as Neo4j or Nebula Graph
• DevOps infrastructure and cloud architecture
• Payment integrations such as Airwallex or Stripe
• Computer vision or VLM systems
• Flutter-facing API design
• Internal developer tools or engineering productivity systems

Years of experience

5–10+ years of relevant engineering experience, with significant experience leading engineering teams. We are particularly interested in candidates who have progressed from strong hands-on engineering into technical leadership and people management.

Experience leading teams building AI, agentic systems, backend platforms or other technically complex products is highly relevant. We care more about the quality of the teams you have led, the systems you have built and the engineering outcomes you have produced than about your job title.

Hiring process

1. Technical and engineering leadership challenge
2. Engineering management and agentic systems interview
3. CTO and leadership interview

Why join us

• High ownership. You will be the senior technical leader for our Vietnam engineering team.
• Direct CTO partnership. Work closely with the CTO on technical direction and major engineering decisions.
• Build the team. Shape engineering culture, standards, processes and team structure as the company grows.
• Cutting-edge systems. Build real agentic and multi-agent AI systems designed for production.
• Technical depth and leadership. Stay close to the technology while having significant influence over people and execution.
• Build from scratch. Help establish the engineering operating model and architecture for a rapidly evolving AI company.
• Global impact. Build systems and teams serving a global market.