Technical Lead: AI-Powered System Integration (GCP)

Role summary

• End-to-end technical leadership on AI-powered SI projects, from design to delivery and support
• Bridges business requirements and technical implementation
• Works with PMs, architects, developers, partners and client stakeholders

Key responsibilities

• Technical leadership:
  • Lead architecture across applications, cloud, data and integrations (cloud-native, microservices, event-driven)
  • Turn business requirements into technical solutions and architecture artifacts
  • Set coding standards and review designs and code for quality, performance and security
  • Define AI-assisted development standards: tool selection, prompt libraries, review checklists for AI-generated code, guardrails for client-sensitive code
  • Architect production-grade multi-agent and agentic systems
  • Establish LLMOps and AI evaluation frameworks
  • Lead foundation model selection and fine-tuning strategy (data, compute cost, governance)
• Delivery:
  • Oversee the full SDLC (design, build, test, deploy, support)
  • Resolve critical technical issues
  • Ensure NFRs are met (availability, scalability, performance, security)
  • Support deployment, migration and environment setup
• Stakeholders:
  • Main technical contact for clients and internal teams
  • Join requirement workshops and design reviews
  • Explain technical concepts to technical and non-technical audiences
• Team:
  • Mentor developers and engineers across full-stack, AI/ML and cloud
  • Drive knowledge sharing, allocate tasks and oversee deliverable quality
• Governance:
  • Ensure compliance with enterprise architecture, security and responsible AI standards
  • Produce documentation (HLD, LLD, ADRs, runbooks, AI model docs)
  • Support audits, risk assessments and governance reviews
• Pre-sales:
  • Provide technical input for proposals, solutioning and estimates
  • Support RFP/RFI responses and client presentations

Experience required

• 8+ years in full-stack engineering, system integration or solution delivery, including 3+ years as a technical lead or principal engineer
• 3+ years leading teams on medium to large cloud and AI projects
• SI or consulting background highly preferred

Technical skills (mandatory)

• Backend:
  • Python, Java, Golang or Node.js
  • REST/GraphQL API design
  • Microservices and middleware integration
  • Message queues, event-driven and async processing
• Frontend:
  • React, Angular or Vue
  • Component design, state management, responsive and cross-browser design
  • Accessibility, performance optimization, UI/UX best practices
  • Tooling such as Webpack and Vite
• AI-assisted development (vibe coding):
  • Tools: GitHub Copilot, Cursor, ChatGPT/Claude, Google Cloud Code Assist (Gemini, Antigravity)
  • Rapid prototyping and prompt engineering for code generation
  • Reviewing, testing and refining AI-generated code while balancing speed, security and maintainability
• Google Cloud Platform:
  • Compute: Compute Engine, Cloud Run, Cloud Functions, GKE
  • Storage and databases: Cloud Storage, Filestore, Cloud SQL, Firestore, Bigtable
  • Data: BigQuery, Dataflow, Pub/Sub
  • Networking: VPC, Cloud Load Balancing, Cloud CDN
  • Security: IAM, Secret Manager, Cloud Armor
  • CI/CD (Cloud Build, Artifact Registry), Docker and Kubernetes/GKE
  • Terraform or Cloud Deployment Manager is a plus
• Google Cloud AI & GenAI:
  • Vertex AI: training, deployment, monitoring, AutoML, fine-tuning, model versioning
  • GenAI: Gemini/PaLM, prompt engineering, RAG, Vertex AI Vector Search and embeddings
  • Vision AI, Speech AI, Natural Language AI, Recommendations AI
  • AI evaluation, monitoring, responsible AI and model governance
• Data & analytics:
  • BigQuery for warehousing, analytics and ML feature engineering
  • Data pipelines (ETL/ELT) and streaming (Pub/Sub, Dataflow)
  • SQL and NoSQL databases
  • Data governance, privacy and security
• DevOps & security:
  • Modern DevOps practices and full-stack security
  • Secure AI, data privacy and compliance
  • Monitoring and observability (Cloud Monitoring, Cloud Logging)

Soft skills

• Strong problem-solving and analytical ability
• Excellent communication and stakeholder management
• Comfortable in fast-paced, multi-project environments
• Collaborative and team-oriented
• Keen to keep up with emerging technology

Nice to have

• Experience with Azure and/or AWS

Responsibilities

1. Business Opportunity

• Identify and pursue new opportunities in the CMP polishing market.

• Support strategic initiatives like conducting Technical Engagement Meeting (TEM) to expand Company’s technical presence in Southeast Asia.

2. Customer Engagement

• Build strong relationships with customers to understand technical and operational needs.

• Present tailored solutions and proposals that demonstrate clear value.

3. Internal Collaboration

• Work closely with R&D/MSE and Business Unit to translate customer requirements into optimized solutions.

• Provide feedback from customer evaluations to guide product improvements.

4. Technical Proposal & Qualification

• Prepare and deliver comprehensive technical proposals.

• Facilitate and support customer onsite product evaluations and qualifications, ensuring successful integration into customer processes.

Requirement

• Bachelor’s or Master’s degree in Engineering, Materials Science, Physics, Chemistry, or a related field. An advanced degree is a plus.

• 5+ years minimum hands-on experience in the field of Semiconductor.

• CMP experience is a must

• Strong technical knowledge of semiconductor manufacturing processes, particularly CMP polishing.

• Proven ability to engage with customers and manage technical discussions.

• Excellent communication and presentation skills, both technical and business-oriented.

• Ability to work collaboratively across cross-functional teams.

• Experience in Southeast Asia’s semiconductor industry is highly desirable

All Successful candidates can expect a very competitive remuneration package and a comprehensive range of benefits.

As a Customer Service Officer, you’ll deliver outstanding service by managing customer interactions both in-person and over the phone.

• Serve as the first point of contact by warmly greeting customers.
• Handle all inbound and outbound calls, log details accurately in the CRM, and apply correct wrap-up codes.
• Collect and update customer details, vehicle registration, and ownership records.
• Verify warranty and support agreements per local guidelines.
• Book appointments across three service centres and offer mobility services.
• Screen technical calls and route them to the appropriate service advisor and payment method.
• Optimize workshop capacity by efficiently assigning vehicles and tasks.
• Provide general advice and set clear expectations for service follow-up.
• Assist in executing product campaigns and service promotions.
• Arrange airport pickup/delivery and schedule car care services.
• Monitor customer waiting times and non-verbal cues to maintain service standards.
• Generate daily, weekly, and monthly reports as needed.
• Hand over vehicle to customers with basic work explanation.

Who We’re Looking For

• Minimum GCE ‘O’ Level or equivalent qualification
• At least 2 years of experience in customer service or call centre support
• Strong communication and customer service skills
• Able to thrive in a fast-paced environment and work well under pressure
• 2 positions available (Alexandra/Ubi) 

All Successful candidates can expect a very competitive remuneration package and a comprehensive range of benefits.

Role Summary

• Lead the design, development, and governance of enterprise AI agents built on Gemini Enterprise and Gemini models
• Own the full agent lifecycle: architecture, grounding, deployment, evaluation, and ongoing governance
• Ensure agents are accurate, safe, compliant, and trusted enough for production use
• Serve as the go-to expert for building agents on Gemini Enterprise and for setting up the governance frameworks that keep them reliable at scale
• Collaborate with the GCP platform team (the underlying infrastructure runs on Google Cloud Platform)

Key Responsibilities

Gemini Enterprise Agent Development

• Design, build, and own multi-agent solutions on Gemini Enterprise (formerly Agentspace), covering architecture, orchestration, task/tool design, and multi-turn conversation flows
• Configure grounding, enterprise search, and data connectors so agents retrieve accurate, up-to-date, and properly scoped information
• Integrate Gemini models (via Gemini API and/or Vertex AI) into agents and downstream applications, tuning prompts, context strategies, and tool/function calling
• Design and productionize RAG pipelines and retrieval strategies for agent grounding
• Evaluate and iterate on agent quality (accuracy, relevance, latency, cost) using structured evaluation frameworks

AI Governance & Responsible Agent Operations

• Define and implement governance frameworks: access control, data permissions, usage policies, and approval workflows for new production agents
• Build guardrails against hallucination, data leakage, prompt injection, and unauthorized data access
• Establish monitoring, logging, and audit trails for agent behavior, including token usage, response quality, and policy violations
• Partner with security, legal, and compliance teams to meet data privacy, residency, and responsible-AI requirements
• Create and maintain documentation, review checklists, and lifecycle standards (build → evaluate → approve → monitor → retire)
• Track Gemini model and Gemini Enterprise releases and assess their impact on existing agents and governance policies

Cross-Functional Collaboration & Automation

• Work with data science, AI engineering, security, and business teams to turn use cases into governed, production-ready agents
• Automate agent configuration, evaluation, and deployment workflows using Python and Gemini Enterprise/Vertex AI APIs and SDKs
• Build internal tooling and dashboards for visibility into agent inventory, usage, and governance status
• Participate in code and design reviews and contribute to shared standards for agent development and governance

Required Skills & Experience

• 7+ years in AI/ML engineering, applied AI, or GenAI platform roles, with hands-on ownership of agent or LLM-application development
• Direct, hands-on experience building and configuring agents on Gemini Enterprise (or Agentspace): agent design, grounding, enterprise search, data connectors
• Strong hands-on experience with Gemini models (Gemini API or Vertex AI): prompting, tool/function calling, context and RAG design
• Practical experience implementing AI governance controls: access management, guardrails, evaluation frameworks, audit logging, and responsible-AI policies
• Solid understanding of LLM application patterns: RAG, embeddings, vector search, multi-agent orchestration
• Solid Python skills for automation, evaluation tooling, and API integration
• Ability to work cross-functionally with data science, security/compliance, and business stakeholders
• Working familiarity with GCP (IAM, Cloud Storage, basic networking)

Preferred / Nice-to-Have

• Google Cloud certifications (Professional Machine Learning Engineer or Professional Cloud Architect)
• Experience with Terraform, Kubernetes (GKE), or CI/CD pipelines
• Experience with monitoring/observability tools (Cloud Monitoring, Prometheus, Grafana, Datadog)
• Familiarity with responsible-AI and model-risk frameworks for enterprise GenAI
• Experience with other enterprise GenAI/agent platforms (e.g., OpenAI, Anthropic, open-source LLM stacks) for comparison

Soft Skills

• Strong governance and risk mindset, balancing agent capability with safety, compliance, and trust
• Clear communicator who can translate technical agent behavior into business and compliance language
• Comfortable with ambiguity amid fast-evolving Gemini features and emerging governance practices
• Ownership mentality, from agent design through deployment, evaluation, and long-term governance

Tech Stack

• Agent Development: Gemini Enterprise (Agentspace), Gemini models, Vertex AI, Model Armor, custom ADK agents, Agent Designer
• AI Governance: Evaluation frameworks, audit/logging tooling, responsible-AI guardrails, IAM/access policies
• Retrieval & Data: RAG pipelines, enterprise search, data connectors, vector search
• Languages: Python (primary), Terraform, JavaScript, Bash
• Cloud Platform (supporting): GCP (IAM, Cloud Storage, networking basics)
• Monitoring: Cloud Monitoring, Cloud Logging, Prometheus, Grafana

We regret that only shortlisted candidates will be notified