AI Technical Lead

Job Description

• We are looking for an experienced Technical Lead to provide end-to-end technical leadership across AI-powered system integration projects.
• The role combines full-stack engineering, Google Cloud Platform, AI/GenAI, system integration, and technical leadership.
• You will work closely with clients, architects, project managers, developers, and partners to design and deliver scalable, secure, cloud-native and AI-enabled solutions.

Key Responsibilities

• Lead technical architecture and solution design across applications, cloud, data, AI and integrations.
• Translate business requirements into scalable technical solutions and architecture.
• Lead end-to-end SDLC delivery covering design, development, testing, deployment and support.
• Design and implement cloud-native, microservices and event-driven architectures.
• Architect production-grade multi-agent and agentic AI systems using suitable orchestration frameworks.
• Establish LLMOps, AI evaluation and model governance frameworks.
• Lead foundation model selection, fine-tuning strategy, data requirements and AI governance.
• Define standards and guardrails for AI-assisted development, including prompt libraries and review of AI-generated code.
• Provide technical guidance across full-stack development, AI/ML integration and cloud engineering.
• Review architecture and code for quality, security, scalability and performance.
• Lead troubleshooting and resolution of complex technical issues.
• Act as the key technical interface with clients and stakeholders.
• Mentor engineers and lead technical capability development.
• Prepare and review technical documentation including HLD, LLD, ADRs, runbooks and AI model documentation.
• Ensure adherence to enterprise architecture, security, compliance and responsible AI standards.
• Support RFP/RFI responses, proposals, estimations and client presentations in an SI/consulting environment.

Mandatory Technical Skills

• Strong hands-on programming experience in Python, Java, Golang or Node.js.
• Strong expertise in REST/GraphQL APIs, microservices, middleware and system integration.
• Experience with message queues, asynchronous processing and event-driven architectures.
• Hands-on experience with React, Angular or Vue.js.
• Good understanding of frontend architecture, state management, API integration and performance optimisation.

AI-Assisted Development

• Hands-on experience with AI-assisted development tools such as:
• GitHub Copilot
• Cursor
• ChatGPT / Claude
• Google Cloud Code Assist / Gemini
• Experience with prompt engineering, rapid prototyping and AI-generated code.
• Strong understanding of validating, testing and securing AI-generated code.

Google Cloud Platform

• Strong hands-on experience with GCP services including:
• Compute Engine, Cloud Run, Cloud Functions, GKE
• Cloud Storage, Filestore
• Cloud SQL, Firestore, Bigtable
• BigQuery, Dataflow, Pub/Sub
• VPC, Load Balancing, Cloud CDN
• IAM, Secret Manager, Cloud Armor
• Experience with Docker, Kubernetes/GKE and CI/CD.
• Experience with Cloud Build and Artifact Registry.
• Terraform experience is an advantage.

Google Cloud AI / GenAI

• Proven hands-on experience with Vertex AI.
• Experience with model training, deployment, monitoring, versioning and fine-tuning.
• Strong experience with Gemini/LLMs, prompt engineering and RAG.
• Experience with embeddings and vector search, preferably Vertex AI Vector Search.
• Exposure to Vision AI, Speech AI and Natural Language AI services.
• Understanding of AI model evaluation, monitoring, responsible AI and governance.

Data & Analytics

• Strong experience with BigQuery and data warehousing.
• Understanding of ETL/ELT, data integration and data pipelines.
• Experience with SQL and NoSQL databases.
• Experience with Pub/Sub and Dataflow.
• Good understanding of data privacy, governance and security.
• DevOps & Security - Strong understanding of DevOps practices and CI/CD.
• Experience with monitoring and observability, including Cloud Monitoring and Cloud Logging.
• Good understanding of cloud security, secure AI practices, data privacy and compliance.

Qualifications & Experience

• 8+ years of hands-on experience in full-stack software engineering, system integration or solution delivery.
• At least 3 years in a Technical Lead
• Minimum 3 years of experience leading technical teams on medium to large-scale cloud and AI projects.
• Experience in System Integration (SI) or consulting environments is highly preferred.
• Strong client-facing and stakeholder management experience.
• Excellent communication, analytical and problem-solving skills.