AI Technical Lead

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

Job summary

Basil Technologies Pte. Ltd. in Singapore seeks an experienced technical leader to drive end-to-end software engineering for cloud, data, and AI-enabled solutions.

You will translate requirements into robust architectures, enforce coding standards, and guide teams across full-stack development, AI integration, and cloud engineering. Lead AI-assisted development and governance efforts, review designs for performance and security, and collaborate with clients and stakeholders to deliver

Qualifications

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

Responsibilities

• 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
• 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.
• Act as the main technical point of contact for clients and internal teams.
• Participate in requirement work shops, technical discussions, and design reviews.
• Communicate technical concepts clearly to both technical and non-technical stakeholders.
• 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 over see quality of deliverables across the technology stack.
• 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.
• 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.

Skills

Full-stack development

AI/ML integration

Cloud architecture

GCP

DevOps

Leadership

Education

Bachelor's degree in CS/Engineering

Tools

Docker

Kubernetes

Terraform

Vertex AI / AI tools

Job description

Key Responsibilities

• 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 work shops, 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 over see 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.

Qualifications

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/Graph QL).
• 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 Copilot or similar AI pair programming assistants
• Cursor IDE or AI-enhanced development environments
• Chat GPT/Claude for 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: Big Query, 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 & Gen AI

• 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
• Auto ML 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 Big Query 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 infast-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