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, workplace 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 (REST/gRPC), security, and data stores (PostgreSQL, Redis, CosmosDB or equivalent).
- Leadership Delivery• Provide technical leadership through architecture reviews, code reviews, mentoring, and close collaboration with product, data science, DevOps, and QA teams.
- • Translate business and product requirements into clear, executable technical plans.
- • Own quality, Development Delivery strategy, and end-to-end accountability.

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