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.