Lead - AI Unit/Senior Lead - AI Unit

Job description

Job Purpose We are looking for a Team Lead to lead the design and development of a conversational AI platform delivered as a mobile SDK and a web application.- This role goes beyond writing code and involves owning system design, architecture patterns, and engineering standards for the platform. • You will work closely with product, AI, security, and DevOps teams to ensure the solution is scalable, secure, and production-ready. • In addition to technical ownership, you will mentor engineers, manage delivery timelines, and ensure the team consistently delivers high-quality outcomes while building a future-ready platform. • uties and ResponsibilitiesSystem Design Architecture• Own the overall technical design of the conversational AI platform across Web UI, Mobile SDK, and backend integrations. • • Define and enforce architecture patterns, design principles, and coding standards across the team. • • Ensure the platform follows capability-driven rendering, channel separation, and security-first design. • • Review and approve technical designs, schemas, and integration approaches. • Delivery Engineering Ownership• Lead end-to-end delivery of features from design to production. • • Balance futuristic UI innovation with performance, security, compliance, and maintainability. • • Ensure auditability, analytics, and observability are built into every user flow. • • Identify technical risks early and drive mitigation plans. • DevOps Operational Readiness• Work with Infra teams on CI/CD pipelines, environment setup, and deployment strategies. • • Ensure smooth releases, rollback mechanisms, and operational stability. • • Monitor production issues and guide root-cause analysis and fixes. • • Drive performance optimization and scalability improvements. • Team Leadership People Management• Lead, mentor, and guide UI and frontend engineers. • • Conduct code reviews, technical coaching, and design walkthroughs. • • Plan work, break down tasks, and ensure timely delivery without compromising quality. • • Foster a culture of ownership, clean coding, and continuous improvement. • Cross-Functional Collaboration• Act as the technical bridge between product, AI, security, and engineering teams. • • Translate product requirements into clear technical execution plans. • • Support stakeholders with technical clarity and realistic trade-off discussions. • ey Decisions / DimensionsArchitecture Platform Design Decisions• Defining overall system architecture for the conversational AI platform across SDK, Web UI, and backend integrations. • • Choosing architecture patterns, design principles, and technology stacks aligned with enterprise scale and compliance. • • Deciding how capabilities, channel separation, and security boundaries are enforced across the platform. • • Determining what functionality is configuration-driven versus custom-built. • Delivery Execution Decisions• Prioritizing features, technical debt, and architectural improvements across release cycles. • • Deciding delivery approaches that minimize inter-team dependency while ensuring quality. • • Defining testing strategies including unit, integration, and end-to-end testing. • • Ensuring all components support feature enable/disable, rollback, and controlled rollout. • DevOps, Stability Risk Decisions• Deciding CI/CD practices, deployment strategies, and release governance in coordination with DevOps teams. • • Ensuring high availability, backup, and disaster recovery considerations are built into the system design. • • Identifying technical risks early and deciding mitigation strategies. • • Making trade-offs between speed of delivery and long-term platform stability. • People Team Decisions• Assigning responsibilities, reviewing designs, and approving code changes. • • Mentoring team members and guiding technical growth. • • Enforcing coding standards, documentation practices, and review discipline. • • Balancing innovation with realistic execution and team capacity. • ajor Challenges• Designing and maintaining a scalable architecture that works across mobile SDKs, WebView-based UI, and public web environments. • • Balancing innovation in conversational and futuristic UI with enterprise requirements such as auditability, security, and regulatory compliance. • • Coordinating across multiple teams including AI, backend, mobile, security, and DevOps with minimal inter-team dependency. • • Managing technical complexity while ensuring consistent delivery timelines and quality standards. • • Making architectural trade-offs between performance, flexibility, cost, and long-term maintainability. • • Ensuring operational stability of a fast-evolving platform in production environments. • • Building and growing a team capable of delivering both cutting-edge UI and enterprise-grade systems. • equired Qualifications and Experience Educational Qualifications• Bachelors or Masters degree in Computer Science, Engineering, or related field. • • 78 years of software engineering experience, including 2+ years in a technical leadership role. • Technical Architectural Skills• Lead end-to-end design, development, and ownership of Conversational AI platforms, covering frontend, backend, AI/LLM orchestration, and enterprise integrations. • • Define and review system architecture using microservices, API-first, and cloud-native patterns to build scalable, secure, and high-availability chatbot solutions. • • Drive integration of AI/LLM capabilities such as intent detection, entity extraction, dialogue management, prompt engineering, and agent-based workflows into production systems. • • Oversee development of reusable SDKs and multi-channel conversational interfaces across web, mobile, and third-party platforms. • • Ensure reliable cloud deployments on AWS/Azure/GCP using CI/CD pipelines, containerization, Kubernetes, monitoring, and cost-optimized infrastructure. • • Guide implementation of backend (Node. • s, Python), frontend (Angular/React), APIs (RE