EPAM Systems
22 hours ago
Platform Engineer — Semantic Discovery & Credentials (mcpreg-004)
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Company information
- Company
- EPAM Systems
- Location
- Portugal Portugal
- Posted
- 22 hours ago
Job description
We're looking for a Platform Engineer — Semantic Discovery & Credentials (mcpreg-004) to join our team in Portugal in a fully remote working mode. In this role, you will build core capabilities for semantic discovery and secure credential management within the MCP Server Registry for an Enterprise Agent Development Platform. This platform provides a cloud-native environment for defining, orchestrating, and observing AI agents at scale, accelerating development by standardizing runtime, tooling, deployment, and observability. Your work will focus on enabling intelligent MCP resource discovery through vector-based search and providing enterprise-grade, secure credential handling integrated with platform services.
Responsibilities
- Design and implement semantic discovery mechanisms for MCP servers using vector embeddings
- Integrate Vault (HashiCorp) and AWS Secrets Manager for secure credential storage and retrieval
- Develop and maintain APIs in Python for credential lifecycle management and retrieval in runtime environments
- Implement domain and capability taxonomy for MCP resource classification
- Build indexing pipelines using OpenSearch or pgvector for semantic search and discovery
- Collaborate on integrating semantic search with MCP orchestration workflows and developer tooling
- Ensure secure handling of keys, tokens, and secrets with enterprise compliance standards
- Optimize performance and reliability of credential management components for large-scale deployments
- Work closely with platform governance teams to embed access control and compliance into credential workflows
Requirements
- 3+ years of experience in platform or backend engineering roles
- Hands-on experience with secrets management platforms such as Vault (HashiCorp) or AWS Secrets Manager
- Practical expertise implementing semantic or vector search (OpenSearch, pgvector, or equivalent)
- Strong skills in Python for backend API design and integration work
- Knowledge of best practices in security, identity, and access management for distributed systems
Nice to have
- Experience using AWS Bedrock embedding models for semantic indexing
- Familiarity with OpenSearch Service or pgvector on RDS for search infrastructure
- Understanding of OAuth token lifecycle management and associated security patterns
- Background in building enterprise-scale registry or resource management platforms
Required skills
- security
- python
- cloud-native
- ai agents
- api design
- hashicorp
- distributed systems
- identity and access management
- opensearch
- platform engineering
- vault
- aws bedrock
- aws secrets manager
- semantic search
- vector search
- pgvector
- embedding models
- developer tooling
- orchestration workflows
- runtime environments
- vector embeddings
- semantic discovery
- credentials management
- mcp server registry
- enterprise agent development platform
- credential lifecycle management
- opensearch service
- pgvector on rds
- oauth token lifecycle management
- enterprise-scale registry
- resource management platforms
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