9 days ago
Bengaluru, IndiaSenior
Responsibilities
- Architect agent reasoning loops, planning, tool-calling, memory, context management, task decomposition, tool selection, and error recovery.
- Build and ship user-facing agent products including chat UIs, IDE extensions, CLI tools, backend APIs, streaming responses, session state, and context handling.
- Integrate agents with VS Code, LSPs, browser extensions, IDEs, and internal systems, and deploy the frontend and backend components.
- Review code and agent designs from two Junior AI Engineers and mentor them toward independent ownership.
- Define agent quality standards and collaborate on CI/CD, monitoring, versioning, rollback, and observability for production agents.
- Own governance standards for security, data access, cost, and quality, and publish prompting, evaluation, and architecture patterns.
- Own the self-service component catalog and support model for citizen developers and spoke teams.
Requirements
- 1-6 years of hands-on experience building LLM or agent systems.
- Strong Python and/or TypeScript skills with the ability to own a service end to end.
- Hands-on experience with agent frameworks or SDKs such as Claude Agent SDK/MCP, LangGraph, AutoGen, or custom orchestration.
- Experience shipping an agentic system to production rather than only building prototypes.
- Solid understanding of traditional machine learning and AI, including classification, regression, clustering, and feature engineering, alongside LLM and agent approaches.
- Experience designing REST, GraphQL, streaming/WebSocket APIs, LLM streaming APIs, SSE/WebSockets, and token-by-token rendering.
- Strong React/TypeScript experience and Node.js or Python backend experience are valuable extras.
- Experience with CI/CD tooling, cloud infrastructure, containers, observability tooling, and LLMOps practices is valuable.
- Familiarity with Microsoft Copilot, Copilot Studio, Azure AI Foundry, AWS Bedrock, authentication, session management, and AI security and compliance is valuable.
- Manufacturing or semiconductor experience and developer enablement or platform-engineering experience are additional advantages.
Benefits
- Real ownership of the architecture and quality bar for agent systems used by real users.
- Mentoring responsibility with visibility into and accountability for the growth of two Junior AI Engineers.
- Global exposure through collaboration with AI and Data Centers of Enablement, integration, platform engineering, security, compliance, CIO, and IT management teams.
- An inclusive work environment with employee resource groups, including the Pride Network Group and global and local Women's groups.
- Equal-opportunity recruitment, accessibility support, reasonable adjustments, and a safe work environment.
Tech Stack
AWSAzureDatadogDockerGitHub ActionsGoogle Cloud PlatformGrafanaGraphQLJenkinsKubernetesNode.jsPrometheusPythonReactTypeScript
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