AI Technical Lead
17000 - 17500 SGDBASIL TECHNOLOGIES PTE. LTD.
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 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
8000 - 14500 SGD
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