Deputy National Lead AI Unit

Pune - India

Monthly Salary: Not Disclosed

Posted on: 3 days ago

Vacancies: 1 Vacancy

Job Summary

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 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.
Duties and Responsibilities	System 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.
Key Decisions / Dimensions	Architecture & 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.
Major 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.
Required 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 ( 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.

Job PurposeWe 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 wil...

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 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.
Duties and Responsibilities	System 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.
Key Decisions / Dimensions	Architecture & 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.
Major 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.
Required 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 ( 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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