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Protiviti

Global consulting on risk, IT, audits

Agentic AI Platform Senior Manager - AgentCore

AI Application EngineeringConfirmed live in the last 24 hours
Full-time$157k - $272k

About the Job

Requirements

  • A bachelor's degree in a relevant discipline, such as Management Information Systems, Information Systems, or Computer Science.
  • At least 7 years of experience working in professional services or industry.
  • AWS Certified Solutions Architect – Associate certification is required.
  • Experience architecting and implementing enterprise agentic AI platforms using Amazon Bedrock and Amazon Bedrock AgentCore.
  • Experience designing AgentCore Runtime, Gateway, Identity, Memory, Observability, and related platform capabilities.
  • Experience designing agent workflows involving tool use, context management, session state, memory, orchestration, and human oversight.
  • Experience defining patterns for agents interacting with enterprise applications, APIs, data platforms, models, knowledge bases, and other agents.
  • Experience establishing architectural standards for scalability, reliability, security, observability, cost management, and operational support.
  • Experience evaluating model, orchestration, and agent-framework options based on client requirements.
  • Experience designing multi-agent and event-driven solutions where required.
  • Experience establishing reusable reference architectures and engineering patterns for production agent deployments.
  • Experience leading architecture decisions about which models, endpoints, data assets, and AI capabilities should reside within Databricks versus AWS-native services.
  • Experience designing integration patterns between AgentCore and Databricks-hosted or Databricks-managed AI capabilities.
  • Experience evaluating model-serving placement based on governance, data proximity, latency, performance, security, lifecycle management, and business requirements.
  • Experience integrating agents with Databricks SQL, Unity Catalog, MLflow, vector search, data pipelines, and model-serving endpoints where appropriate.
  • Experience designing secure OAuth, service-principal, identity-passthrough, and machine-to-machine authentication patterns.
  • Experience establishing approaches for model registration, versioning, deployment, monitoring, evaluation, and governance.
  • Experience enabling agents to access governed enterprise data and functions without bypassing established Databricks controls.
  • Experience aligning agent architectures with enterprise lakehouse and data-governance strategies.
  • Experience designing and developing reusable AWS Cloud Development Kit constructs for AgentCore environments.
  • Experience building infrastructure patterns for runtimes, gateways, identity, networking, observability, security controls, and enterprise integrations.
  • Experience creating deployment templates applicable consistently across client accounts and environments.
  • Experience establishing automated build, test, security-validation, and deployment pipelines.
  • Experience developing abstractions, configuration models, defaults, and extension points for technical teams.
  • Experience conducting code reviews and ensuring constructs meet engineering, security, reliability, and maintainability standards.
  • Experience defining environment-promotion, versioning, rollback, and release-management approaches.
  • Experience implementing IAM, VPC networking, private connectivity, encryption, secrets management, logging, and monitoring controls with cloud security teams.
  • Experience troubleshooting complex integration, permissions, deployment, and runtime issues.
  • Experience enabling MCP services through AgentCore Gateway.
  • Experience securely connecting agents to enterprise tools, APIs, Lambda functions, HTTP services, data platforms, and MCP servers.
  • Experience designing inbound and outbound authentication patterns for AgentCore and third-party platforms.
  • Experience configuring gateways, targets, credential providers, authorization controls, and tool-discovery patterns.
  • Experience developing reusable integration patterns for exposing enterprise services as agent-accessible tools.
  • Experience establishing controls for MCP tool registration, discovery, access, versioning, testing, and lifecycle management.
  • Experience designing fine-grained permissions and least-privilege access for agents and tools.
  • Experience addressing security requirements for tool invocation, sensitive-data handling, credential management, and auditability.
  • Ability to work in person in local offices and client sites, and travel locally or out of state based on project needs and client requests.

Responsibilities

  • Lead complex agentic AI platform engagements from architecture through production enablement.
  • Serve as the technical lead for Amazon Bedrock and AgentCore implementations.
  • Architect and implement enterprise agentic AI platforms using Amazon Bedrock and Amazon Bedrock AgentCore.
  • Lead the design of AgentCore Runtime, Gateway, Identity, Memory, Observability, and related platform capabilities.
  • Design agent workflows involving tool use, context management, session state, memory, orchestration, and human oversight.
  • Define patterns for agents interacting with enterprise applications, APIs, data platforms, models, knowledge bases, and other agents.
  • Establish architectural standards for scalability, reliability, security, observability, cost management, and operational support.
  • Evaluate model, orchestration, and agent-framework options based on client requirements rather than using a single default platform pattern.
  • Design multi-agent and event-driven solutions where required.
  • Establish reusable reference architectures and engineering patterns for production agent deployments.
  • Lead architecture decisions about which models, endpoints, data assets, and AI capabilities should reside within Databricks versus AWS-native services.
  • Design integration patterns between AgentCore and Databricks-hosted or Databricks-managed AI capabilities.
  • Evaluate model-serving placement based on governance, data proximity, latency, performance, security, lifecycle management, and business requirements.
  • Integrate agents with Databricks SQL, Unity Catalog, MLflow, vector search, data pipelines, and model-serving endpoints where appropriate.
  • Design secure OAuth, service-principal, identity-passthrough, and machine-to-machine authentication patterns.
  • Establish approaches for model registration, versioning, deployment, monitoring, evaluation, and governance.
  • Enable agents to access governed enterprise data and functions without bypassing established Databricks controls.
  • Partner with data and AI teams to align agent architectures with enterprise lakehouse and data-governance strategies.
  • Design and develop reusable AWS Cloud Development Kit constructs for AgentCore environments.
  • Build infrastructure patterns for runtimes, gateways, identity, networking, observability, security controls, and enterprise integrations.
  • Create deployment templates that can be applied consistently across client accounts and environments.
  • Establish automated build, test, security-validation, and deployment pipelines.
  • Develop abstractions, configuration models, defaults, and extension points for technical teams.
  • Conduct code reviews and ensure constructs meet engineering, security, reliability, and maintainability standards.
  • Define environment-promotion, versioning, rollback, and release-management approaches.
  • Partner with cloud security teams to implement IAM, VPC networking, private connectivity, encryption, secrets management, logging, and monitoring controls.
  • Troubleshoot complex integration, permissions, deployment, and runtime issues.
  • Lead the enablement of MCP services through AgentCore Gateway.
  • Connect agents securely to enterprise tools, APIs, Lambda functions, HTTP services, data platforms, and MCP servers.
  • Design inbound and outbound authentication patterns for AgentCore and third-party platforms.
  • Configure gateways, targets, credential providers, authorization controls, and tool-discovery patterns.
  • Develop reusable integration patterns for exposing enterprise services as agent-accessible tools.
  • Establish controls for MCP tool registration, discovery, access, versioning, testing, and lifecycle management.
  • Design fine-grained permissions and least-privilege access for agents and tools.
  • Address security requirements for tool invocation, sensitive-data handling, credential management, and auditability.
  • Partner with clients to identify and manage risk, develop strategies for complex business problems, and devise solutions to support client needs.
  • Build lasting relationships with client personnel through quality product delivery, foster a business-community network, and represent Protiviti in the market.
  • Mentor teams and provide performance development while overseeing successful completion of project work plans.
  • Contribute to client proposals and strategies to win new business.
  • Identify opportunities to integrate product solutions and resources to improve client service capabilities.

Desired Qualifications

  • AWS Certified Solutions Architect – Professional certification.

About the Company

Protiviti

Global consulting on risk, IT, audits

Protiviti is a global consulting firm that helps large organizations tackle risk, compliance, technology, and process challenges. It delivers tailored engagements—often long-term partnerships—drawing on experts in risk and compliance, IT consulting, internal audit, and business process improvement, including legal advisory. In technology, Protiviti assists with digital transformation, cybersecurity, and data analytics; in risk and compliance, it helps manage regulatory requirements and internal controls. Its goal is to help clients strengthen governance, reduce risk, optimize operations, and improve performance across industries, including many Fortune 1000 and Global 500 companies.

Company size
10,001+
Company stage
Not listed
Total funding
Not listed
Headquarters
Menlo Park, CA
Founded
2002

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