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Were building foundational infrastructure to secure AI agents including their identities, access patterns, and interactions with sensitive systems and data. This includes designing intelligent, dynamic mechanisms for ephemeral access control, secrets management, and agent/user identity tailored to modern agent frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, and beyond.

Youll help define how agents (both machine and human-facing) authenticate, receive scoped access, perform actions securely, and leave behind a verifiable audit trail.

This is a unique opportunity to be part of a start-up inside the company building the platform from scratch at one of the most cutting-edge intersections of AI, identity, and security.

Responsibilities:

Develop secure, scalable Python services to support agent identity, secrets access, credential management, and authorization flows.
Implement JWT-based agent/user authentication, and real-time policy checks based on agent context and tool usage.
Build SDKs, wrappers, and tool integrations that enable popular agent frameworks (LangChain, LangGraph, Semantic Kernel, etc.) to securely request and use secrets.
Collaborate closely with the architect and other engineers to design components with clear boundaries and clean contracts.
Ensure secrets and credentials are injected only when needed, redacted from logs, and never persist in agent memory or prompts.
Write thorough tests and maintain high-quality, well-documented code.
Work cross-functionally with internal platform, AI, and security teams to understand requirements and refine implementation plans.

Were building foundational infrastructure to secure AI agents including their identities, access patterns, and interactions with sensitive systems and data. This includes designing intelligent, dynamic mechanisms for ephemeral access control, secrets management, and agent/user identity tailored to modern agent frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, and beyond.

As the Team Lead, youll not only help define how agents authenticate, receive scoped access, perform actions securely, and leave behind a verifiable audit trail youll also be responsible for building and leading a high-impact engineering team from the ground up.

This is a unique opportunity to be part of a start-up inside the company, delivering the platform from scratch at one of the most cutting-edge intersections of AI, identity, and security.

Responsibilities:

Lead the end-to-end development of a secure platform for managing AI agents identities, permissions, access control, and execution context.
Recruit, onboard, and mentor a team of engineers, shaping the teams culture and technical direction.
Drive the design and implementation of core services, ensuring high performance, security, and maintainability.
Enforce engineering excellence and best practices, including testing, code reviews, observability, secure coding, and CI/CD pipelines.
Stay hands-on: actively contribute to critical paths in architecture, prototyping, and complex problem-solving.
Ensure your teams deliverables meet high standards of performance, resilience, and security in production.

We are looking for a highly skilled and experienced Senior Software Engineer with strong backend expertise in Python, hands-on knowledge of modern frontend frameworks like React, and cloud-native development using serverless architectures. The ideal candidate thrives in production environments, has a strong technical orientation, and enjoys contributing across the full stackincluding infrastructure and cross-solution integration tasks.

Design, develop, and maintain scalable backend services using Python
Build responsive and maintainable user interfaces using React
Work with cloud-native serverless technologies in AWS
Collaborate across teams on cross-solution tasks, including Terraform infrastructure integrations, CI/CD improvements, automation, and shared code tooling
Contribute to production excellenceengaging in error analysis, observability, monitoring, and incident response
Utilize monitoring and observability tools such as Datadog and AWS CloudWatch
Champion DevSecOps practices, enforcing security in code, infrastructure, and deployments
Stay current with emerging technologies, proactively propose improvements, and present PoCs or demos to stakeholders
Foster a culture of knowledge sharing, code reviews, and continuous improvement