Technical Lead

APAR TECHNOLOGIES PTE. LTD.; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

APAR Technologies PTE. LTD. is seeking a Technical Lead to drive end-to-end AI-powered system integration projects. You will combine strong full-stack development skills with deep Google Cloud and AI service expertise to design scalable, secure solutions for clients.

You will mentor engineers, collaborate with stakeholders, and establish governance, LLMOps, and best practices for responsible AI while championing fast, high-quality delivery in a dynamic, multi-project environment.

Qualifications

• 8+ years of hands-on software engineering experience with at least 3 years in lead or principal roles.
• Proven ability to lead technical teams on cloud and AI projects in medium to large scale environments.
• Experience in SI or consulting environments is highly preferred.

Responsibilities

• Provide end-to-end technical leadership across AI-powered system integration projects.
• Lead solution design, delivery, and support with scalable, secure architectures.
• Mentor developers and engineers across full-stack, AI/ML, and cloud domains.
• Ensure adherence to governance, security, and responsible AI standards.

Skills

Full-stack engineering

Technical leadership

Cloud & AI technology

SI/Consulting experience

Tools

Python

Java

Golang

Node.js

REST/GraphQL

Microservices

CI/CD

GCP

Kubernetes

Job description

Requirements Experience

• Minimum 8 years of hands-on experience in full-stack software engineering, system integration, or solution delivery, with at least 3 years in a technical lead or principal engineer capacity.
• Minimum 3 years of demonstrated experience leading technical teams in medium to large projects involving cloud and AI technologies.
• Experience in SI or consulting environments is highly preferred.

Full-Stack Development Capability(Mandatory) Backend Development:

• Strong programming experience in Python, Java, Golang, or Node.js.
• Expertise in API design and development (REST/GraphQL).
• Solid understanding of microservices architecture and middleware integration.
• Experience with message queues, event-driven architectures, and asynchronous processing.
• Knowledge of backend frameworks and design patterns.

Frontend Development:

• Hands-on experience with modern frontend frameworks such as React, Angular, or Vue.
• Strong understanding of frontend architecture, component design, and state management.
• Experience with responsive design, cross-browser compatibility, and API integration.
• Familiarity with UI/UX best practices, performance optimization, and accessibility standards.
• Knowledge of modern frontend tooling (Webpack, Vite, etc.).

AI-Assisted Development (Vibe Coding):

• Must have hands-on experience with AI-assisted coding tools and practices.
• Proficiency with tools such as:- GitHub Copilotor similar AI pair programming assistants
• Cursor IDEor AI-enhanced development environments
• ChatGPT/Claudefor code generation and problem-solving
• Google Cloud Code Assist(Gemini, Antigravity etc)

Experience with:

• Rapid prototyping using AI-generated code
• Prompt engineering for code generation
• Code review and refinement of AI-generated solutions
• Accelerated development workflows using AI assistance

Understanding of best practices for:

• Validating and testing AI-generated code
• Maintaining code quality while using AI tools
• Balancing speed with security and maintainability
• Effective prompt crafting for development tasks

Google Cloud Platform

• Strong understanding and experience using core GCP services:- Compute:Compute Engine, Cloud Run, Cloud Functions, GKE (Google Kubernetes Engine)
• Storage:Cloud Storage, Filestore
• Databases:Cloud SQL, Firestore, Bigtable
• Data Analytics:BigQuery, Dataflow, Pub/Sub
• Networking:VPC, Cloud Load Balancing, Cloud CDN
• Security IAM:Identity and Access Management, Secret Manager, Cloud Armor
• Experience with CI/CD pipelines on GCP (Cloud Build, Artifact Registry).
• Hands-on experience with containers (Docker) and orchestration (Kubernetes/GKE).
• Infrastructure as Code experience (Terraform, Cloud Deployment Manager) is a plus.

Google Cloud AI GenAI

• Must have proven experience working with Google Cloud AI and Generative AI services.
• Hands-on experience with Vertex AI including:
  • Model training, deployment, and monitoring
  • AutoML capabilities
  • Custom model development and fine-tuning
  • Model versioning and lifecycle management
• Experience integrating Google Cloud AI services:
  • Generative AI:LLMs (PaLM API, Gemini), prompt engineering, RAG patterns
  • Vision AI:OCR, image classification, object detection
  • Speech AI:Speech-to-Text, Text-to-Speech
  • Natural Language AI:sentiment analysis, entity extraction, translation
  • Recommendations AI
• Strong Understanding of:
  • Prompt engineering and optimization
  • RAG (Retrieval-Augmented Generation) architectures
  • Vector search and embeddings (Vertex AI Vector Search)
  • AI model evaluation and monitoring
  • Responsible AI practices and model governance

Data Analytics

• Strong experience with BigQuery for data warehousing, analytics, and ML feature engineering.
• Understanding of data pipelines, ETL/ELT processes, and data integration patterns.
• Experience with both SQL and NoSQL databases.
• Familiarity with data streaming (Pub/Sub, Dataflow).
• Understanding of data governance, privacy, and security best practices.

DevOps Security

• Experience with modern DevOps practices and tools.
• Understanding of security best practices across the full stack.
• Knowledge of secure AI practices, data privacy, and compliance requirements.
• Experience with monitoring and observability tools (Cloud Monitoring, Cloud Logging).

Soft Skills

• Strong problem-solving and analytical skills with ability to tackle complex full-stack and AI challenges.
• Excellent communication and stakeholder management abilities.
• Ability to explain technical concepts to both technical and non-technical audiences.
• Ability to work effectively in fast-paced, multi-project environments.
• Passion for learning and staying current with emerging technologies in full-stack development, cloud, and AI.
• Strong collaboration skills and team-oriented mindset.

Nice to Have

• Experience in other popular cloud platform such as Azure and AWS

Role Overview

The Technical Lead is responsible for providing end-to-end technical leadership across AI-powered system integration projects, from solution design through delivery and support. This role requires strong full-stack development capabilities combined with deep expertise in Google Cloud Platform and AI services. The Technical Lead bridges business requirements and technical implementation, ensuring scalable, secure, and intelligent solutions for clients. This role works closely with project managers, architects, developers, partners, and client stakeholders.

Key Responsibilities

Technical Leadership

• Lead technical design and architecture across applications, cloud, data, and integrations.
• Translate business and functional requirements into technical solutions and architecture artifacts.
• Define and enforce coding standards, design principles, and best practices.
• Define AI-assisted development standards: tool selection, prompt libraries, code-review checklists for AI-generated output, and guardrails for handling client-sensitive code in AI tool contexts
• Review solution designs and code to ensure quality, performance, and security.
• Provide guidance on modern architectures (cloud-native, microservices, event-driven).
• Architect production-grade multi-agent and agentic systems using orchestration frameworks
• Establish LLMOps and AI evaluation frameworks
• Lead foundation model selection and fine-tuning strategy with understanding of data requirements, compute costs, and governance implications

Delivery Implementation

• Oversee end-to-end technical delivery across the SDLC (design, build, test, deploy, support).
• Troubleshoot critical technical issues and provide resolution guidance.
• Ensure solutions meet NFRs (availability, scalability, performance, security).
• Support deployment, migration, and environment setup activities.

Stakeholder Management

Act as the main technical point of contact for clients and internal teams.

• Participate in requirement workshops, technical discussions, and design reviews.
• Communicate technical concepts clearly to both technical and non-technical stakeholders.

Team Leadership

• Guide and mentor developers and engineers across full-stack development, AI/ML integration, and cloud engineering.
• Support capability building and knowledge sharing within the team.
• Allocate technical tasks and oversee quality of deliverables across the technology stack.

Governance Compliance

• Ensure adherence to enterprise architecture, security, compliance, and responsible AI standards.
• Contribute to technical documentation such as HLD, LLD, ADRs, runbooks, and AI model documentation.
• Support audits, risk assessments, and governance reviews related to AI, data, and cloud solutions.

Pre-Sales Support (SI Context)

• Provide technical input for proposals, solutioning, and estimations for full-stack AI projects.
• Support RFP/RFI responses and client presentations with technical expertise in Applications, Google Cloud and AI.

EA Number : 11C4879