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.

Duties and Responsibilities
System Design Architecture
- Own the overall technical design of the conversational AI platform across Web UI, Mobile SDK, and backend integrations.
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- Define and enforce architecture patterns, design principles, and coding standards across the team.
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- Ensure the platform follows capability-driven rendering, channel separation, and security-first design.
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- Review and approve technical designs, schemas, and integration approaches.
- br/>Delivery Engineering Ownership
- Lead end-to-end delivery of features from design to production.
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- Balance futuristic UI innovation with performance, security, compliance, and maintainability.
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- Ensure auditability, analytics, and observability are built into every user flow.
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- Identify technical risks early and drive mitigation plans.
- br/>DevOps Operational Readiness
- Work with Infra teams on CI/CD pipelines, environment setup, and deployment strategies.
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- Ensure smooth releases, rollback mechanisms, and operational stability.
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- Monitor production issues and guide root-cause analysis and fixes.
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- Drive performance optimization and scalability improvements.
- br/>Team Leadership People Management
- Lead, mentor, and guide UI and frontend engineers.
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- Conduct code reviews, technical coaching, and design walkthroughs.
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- Plan work, break down tasks, and ensure timely delivery without compromising quality.
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- Foster a culture of ownership, clean coding, and continuous improvement.
- br/>Cross-Functional Collaboration
- Act as the technical bridge between product, AI, security, and engineering teams.
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- Translate product requirements into clear technical execution plans.
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- Support stakeholders with technical clarity and realistic trade-off discussions.
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Key Decisions / Dimensions

Architecture Platform Design Decisions
- Defining overall system architecture for the conversational AI platform across SDK, Web UI, and backend integrations.
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- Choosing architecture patterns, design principles, and technology stacks aligned with enterprise scale and compliance.
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- Deciding how capabilities, channel separation, and security boundaries are enforced across the platform.
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- Determining what functionality is configuration-driven versus custom-built.
- br/>Delivery Execution Decisions
- Prioritizing features, technical debt, and architectural improvements across release cycles.
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- Deciding delivery approaches that minimize inter-team dependency while ensuring quality.
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- Defining testing strategies including unit, integration, and end-to-end testing.
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- Ensuring all components support feature enable/disable, rollback, and controlled rollout.
- br/>DevOps, Stability Risk Decisions
- Deciding CI/CD practices, deployment strategies, and release governance in coordination with DevOps teams.
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- Ensuring high availability, backup, and disaster recovery considerations are built into the system design.
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- Identifying technical risks early and deciding mitigation strategies.
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- Making trade-offs between speed of delivery and long-term platform stability.
- br/>People Team Decisions
- Assigning responsibilities, reviewing designs, and approving code changes.
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- Mentoring team members and guiding technical growth.
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- Enforcing coding standards, documentation practices, and review discipline.
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- Balancing innovation with realistic execution and team capacity.
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Major Challenges
- Designing and maintaining a scalable architecture that works across mobile SDKs, WebView-based UI, and public web environments.
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- Balancing innovation in conversational and futuristic UI with enterprise requirements such as auditability, security, and regulatory compliance.
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- Coordinating across multiple teams including AI, backend, mobile, security, and DevOps with minimal inter-team dependency.
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- Managing technical complexity while ensuring consistent delivery timelines and quality standards.
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- Making architectural trade-offs between performance, flexibility, cost, and long-term maintainability.
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- Ensuring operational stability of a quick-evolving platform in production environments.
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- Building and growing a team capable of delivering both cutting-edge UI and enterprise-grade systems.
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Required
Qualifications and Experience

Educational Qualifications
- Bachelors or Masters degree in Computer Science, Engineering, or related field.
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- 78 years of software engineering experience, including 2+ years in a technical leadership role.
- br/>Technical Architectural Skills
- Lead end-to-end design, development, and ownership of Conversational AI platforms, covering frontend, backend, AI/LLM orchestration, and enterprise integrations.
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- Define and review system architecture using microservices, API-first, and cloud-native patterns to build scalable, secure, and high-availability chatbot solutions.
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- Drive integration of AI/LLM capabilities such as intent detection, entity extraction, dialogue management, prompt engineering, and agent-based workflows into production systems.
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- Oversee development of reusable SDKs and multi-channel conversational interfaces across web, mobile, and third-party platforms.
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- Ensure reliable cloud deployments on AWS/Azure/GCP using CI/CD pipelines, containerization, Kubernetes, monitoring, and cost-optimized infrastructure.
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- Guide implementation of backend (Node.
- s, Python), frontend (Angular/React), APIs (REST/gRPC), security, and data stores (PostgreSQL, Redis, CosmosDB or equivalent).
- br/>Leadership Delivery
- Provide technical leadership through architecture reviews, code reviews, mentoring, and close collaboration with product, data science, DevOps, and QA teams.
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- Translate business and product requirements into clear, executable technical plans.
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- Own quality, Development Delivery strategy, and end-to-end accountability.
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📌 Lead - AI Unit/Senior Lead - AI Unit (Pune)
🏢 Bajaj Finance
📍 Pune