Team Lead - Agentic Systems

RingCentral; Bengaluru; Hybrid; INR 300,000 - 540,000; Full time

Job summary

RingCentral in Bengaluru seeks a seasoned Team Lead – Agentic Systems to guide an engineering team building autonomous AI applications, AI Agents, and AI Automations. You will translate business vision into production AI systems while mentoring engineers.

You will own end-to-end architecture of production-grade multi-agent workflows, implement guardrails, and drive best practices across integrations with enterprise SaaS and APIs. Hybrid work mode.

Qualifications

• 8 years of professional software engineering experience, with 1–2 years in hands-on LLM or agentic frameworks.
• 1+ years direct team leadership or mentoring.
• Strong proficiency in Python and/or Node.js.
• Familiarity with OpenAI/Anthropic and LangChain/LangGraph.
• Experience building LLM apps, including prompt engineering and tool calls.
• Experience with RAG, vector databases, and state management.
• Experience with enterprise SaaS integrations and REST APIs.

Responsibilities

• Lead and grow a team of AI and software engineers; oversee code reviews and sprint execution.
• Own architecture and reliability of autonomous AI agents and workflows.
• Define standards for LLM orchestration and tool integration.
• Develop evaluation harnesses and production observability.
• Implement guardrails, access control, and governance across multi-tool systems.
• Collaborate with Product, Security, and Infrastructure to align capabilities.

Skills

LLM orchestration

Team leadership

Python

Node.js

LangChain

LangGraph

RAG pipelines

API integration

Tool integration

SQL/NoSQL

Testing harnesses

AI security

Tools

REST APIs

Vector databases

Embedding search

Docker

CI/CD

Job description

We are seeking a seasoned Team Lead – Agentic Systems to guide and mentor an engineering team in building, scaling, and productionizing enterprise-grade autonomous AI applications, AI Agents, and AI Automations. In this role, you will combine hands-on technical expertise in LLM orchestration, RAG pipelines, and agentic workflows with team leadership—driving best practices, system reliability, and architectural standards across multi-agent enterprise deployments. You will translate business vision into production AI systems while fostering team growth and continuous technical improvement.

Work Mode: Hybrid

Key Responsibilities

• Lead, mentor, and grow a team of AI and software engineers; perform regular code reviews, manage sprint execution, and drive career development and hiring.
• Own the end-to-end architecture, delivery, and operational reliability of production-grade, autonomous AI agents, multi-agent teams, and workflow automations.
• Work with ARB to establish standards and design patterns for LLM orchestration (LangChain, LangGraph, etc.), tool/API integration, state management, and multi-step reasoning systems.
• Define and implement continuous evaluation harnesses and production observability.
• Implement enterprise-grade guardrails, access control boundaries, prompt injection defense, and governance across multi-tool, multi-agent systems.
• Lead the engineering of advanced Retrieval-Augmented Generation (RAG) pipelines, integrating vector databases, hybrid search, and structured/unstructured enterprise data stores.
• Build and maintain agent integrations with enterprise applications across multiple business use cases, via REST APIs, connector frameworks, or MCP-style tool registries.
• Operate within existing access-control, logging, and audit patterns for multi-tool agent systems; flag gaps to the architecture team rather than redesigning independently
• Collaborate closely with Product, Security, Enterprise Architecture, and Infrastructure teams to align agentic capabilities with strategic business use cases.

Required Skills (Must Have)

• 8 years of professional software engineering experience, including at least 1–2 years of hands-on building with LLMs or agentic frameworks.
• 1+ years of experience in direct team leadership, technical mentorship, or managing small-to-medium-sized engineering teams.
• Strong proficiency in Python and/or Node.js for AI and backend development.
• Working knowledge of major LLM providers (e.g., OpenAI, Anthropic) and prompt orchestration frameworks (LangChain, LangGraph).
• Hands-on expertise in building LLM applications, including
• Prompt engineering and enforcing structured outputs
• Tool integration and function calling
• Retrieval-Augmented Generation (RAG) using vector databases and embedding-based search
• Designing multi-agent workflows and orchestration frameworks
• Managing context windows and conversational state
• Experience integrating external tools and APIs via function calling or tool-registration mechanisms.
• Experience integrating agents or tools with enterprise SaaS applications via REST APIs or connector frameworks.
• Working knowledge of SQL and NoSQL databases and how they plug into AI pipelines.
• Experience writing test cases or evaluation harnesses for agent/LLM behavior (accuracy, hallucination, tool-call correctness).
• Familiarity with agent evaluation techniques, including LLM-as-a-judge, task-based evaluations, benchmark design, and automated regression testing.
• Understanding of access-control and audit-logging patterns in multi-tool, multi-agent systems.
• Understanding of AI security, prompt injection, data leakage, permission boundaries, and agentic-system guardrails.
• Strong debugging skills and the ability to implement complex multi-step systems within an established architecture.

Nice to Have Skills

• Understanding of cloud deployment and infrastructure (AWS, GCP).
• Knowledge of containerization and CI/CD pipelines (Docker, GitHub Actions).
• Experience with AI observability, guardrails, and safety mechanisms for LLMs.
• Familiarity with data warehouses or analytical query engines for large-scale structured retrieval.
• Background in enterprise SaaS integration patterns and multi-tenant system design.