Platform Engineer

We are looking for a Platform Engineer to build secure discovery and credential management capabilities for enterprise AI platforms. The role focuses on semantic search, vector-based discovery, secrets management, credential access services, and AI tool classification. The ideal candidate has hands-on experience with Python backend development, secrets management solutions, and modern semantic search technologies.

What you will do

• Design and implement semantic discovery capabilities for MCP servers, tools, and agent ecosystems.
• Build and maintain vector-based search solutions using embeddings, OpenSearch, pgvector, or similar technologies.
• Develop metadata taxonomies and capability classification models for MCP services and AI tools.
• Design and implement secure credential retrieval services using Python and cloud-native architectures.
• Integrate HashiCorp Vault and AWS Secrets Manager to support secure secret storage and access management.
• Build APIs for credential retrieval, access validation, and secure secret consumption.
• Implement governance controls for credentials, service identities, and tool access policies.
• Design semantic indexing pipelines and relevance-ranking strategies for discovery services.
• Collaborate with platform, security, and AI engineering teams to establish discovery and credential management standards.
• Implement observability, auditability, and monitoring for secret access and discovery workflows.
• Support lifecycle management of credentials, service identities, and access tokens across distributed systems.
• Produce technical documentation, architecture guidelines, and operational playbooks.

What you need for this

• Semantic discovery implementation (vector embeddings, OpenSearch or pgvector)
• Vault (HashiCorp) integration for credential management
• AWS Secrets Manager as an alternative
• Python credential retrieval API
• MCP server capability and semantic domain taxonomy

Experience:

• 4+ years platform or backend engineering
• Secrets management (Vault or AWS Secrets Manager)
• Vector search or semantic search implementation

Will be a plus:

• AWS Bedrock embedding models for semantic indexing
• OpenSearch Service or pgvector on RDS
• OAuth token lifecycle management