# AI Data Engineering - Forward-Deployed Engineers (FDEs)

> Source: https://ibl.ai/service/data-engineering/government

Forward-Deployed Engineers build your MCP-powered agency memory layer for AI agents — with your data, in your environment.

Build your agency "memory layer" for AI agents — powered by the Model Context Protocol (MCP) — with your data, in your environment.

## What This Is

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ibl.ai's Forward-Deployed Engineers embed with your team to connect HRIS, LMS, case management, ERP, identity, storage, and regulatory systems into a secure, policy-aware memory layer built on the Model Context Protocol (MCP). That memory becomes the backbone for AI agents — workforce coaches, program assistants, and citizen-service tools — running privately in your infrastructure.

This is professional services, billed by the hour (ultra-competitive rates), with clear milestones and artifacts you own.

## Built on the Model Context Protocol (MCP)

### What is MCP?

The Model Context Protocol is an open standard — originally developed by Anthropic — that defines how AI models connect to external data sources, tools, and services. MCP provides a universal interface between AI agents and your agency systems, replacing brittle custom integrations with standardized, secure connectors.

Think of MCP as USB-C for AI: one protocol, every system. Instead of building a custom integration for each HRIS, LMS, or case management system, MCP gives agents a single, consistent way to read data, call tools, and respect permissions across your entire agency stack.

### Why MCP Matters for Government Agencies

Agency IT teams maintain dozens of systems — USA Staffing, DCPDS, Cornerstone for Government, ServiceNow, and more. Traditional integration approaches require point-to-point connectors that break with every vendor update. MCP eliminates this fragility by providing a protocol-level contract between AI agents and data sources.

With MCP, your agency gets portable agents that work across any LLM provider (OpenAI, Anthropic, Google, Meta, or air-gapped local models), interchangeable connectors that can be swapped without rewriting agent logic, and built-in security boundaries where every data access goes through policy-aware middleware with federal-grade controls.

### MCP Architecture at ibl.ai

Every ibl.ai deployment uses MCP as the core integration protocol. Our Forward-Deployed Engineers build MCP servers for each agency system — HRIS, LMS, case management, ERP, identity providers, and document stores. These MCP servers expose structured tools and resources that agents can discover and invoke at runtime.

The result is a composable agent architecture: a workforce coaching agent can query personnel records from DCPDS, fetch training completions from FedVTE, check certification expirations, and retrieve regulatory guidance — all through MCP — without any custom glue code between systems.

## MCP Servers We Build

### HRIS MCP Server (USA Staffing, DCPDS, Workday Government)

Exposes personnel records, position classifications, clearance levels, service history, and performance ratings as MCP resources.

Agents can query real-time workforce data without direct database access. Field-level classification controls and need-to-know enforcement determine who sees what based on role and clearance.

### LMS MCP Server (Cornerstone for Government, Percipio, FedVTE, AgLearn)

Provides training catalogs, completion records, mandatory training status, certification tracking, and competency assessments as MCP tools.

Agents can retrieve specific training materials, check compliance deadlines, and access agency-level analytics — all scoped to the requesting user's permissions and clearance level.

### Case Management MCP Server (ServiceNow Gov, Salesforce Government Cloud)

Connects citizen service requests, program cases, inter-agency referrals, and compliance tracking. Agents can look up case status, pull program eligibility data, and surface performance metrics for mission reporting.

### Identity & Directory MCP Server (PIV/CAC via Entra ID, Okta for Government)

Provides role resolution, clearance verification, group memberships, and authentication context. MCP-level RBAC ensures agents only access data appropriate for the authenticated user's role and clearance — analyst, program manager, contracting officer, or agency CISO.

### Document & Storage MCP Server (GovCloud S3, DISA Storage, SharePoint Gov)

Indexes agency documents — directives, regulations, standard operating procedures, policy memoranda — and makes them retrievable via semantic search through MCP.

Agents can cite specific documents with page-level provenance rather than generating answers from training data alone. Classification-aware retrieval ensures CUI/FOUO handling.

### Custom MCP Servers

We build MCP servers for any system with an API or database: ERP/Finance (SAP S/4HANA Public Sector, Oracle Federal Financials), grants management, procurement systems, GIS platforms, and more. If your agency has it, we can connect it.

## MCP Security and Governance

### Protocol-Level Access Control

Every MCP request carries authentication context — who is asking, what role and clearance they hold, and what need-to-know has been established. Our MCP middleware enforces field-level permissions before data ever reaches the agent.

An employee asking about their own training sees their records; a supervisor querying the same system sees their directorate; an agency admin sees aggregate analytics. Same MCP server, different views.

### PII Masking and Data Classification

MCP responses pass through a policy engine that redacts sensitive fields based on configurable rules and data classification levels. Social security numbers, clearance details, and CUI-marked content are masked or excluded from agent context unless explicitly authorized by policy.

Every redaction and classification decision is logged for audit.

### Audit Trails and Compliance

Every MCP tool invocation is logged with timestamp, requesting agent, authenticated user, data accessed, and response summary.

These audit trails support NIST 800-53 compliance reviews, NIST 800-53 control assessments, IG audits, and incident response. Logs are stored in your infrastructure and retained per your agency records schedule.

### Sandboxed Execution

MCP servers run in isolated containers within your GovCloud VPC, on-premises infrastructure, or IL4/IL5 enclaves. No agency data leaves your environment.

Agents interact with MCP servers over internal networks with mTLS encryption. Air-gapped deployment options ensure LLM inference stays within your security boundary.

## Who We Work With

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Agency CIO / IT & Enterprise Architecture

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Chief Learning Officer / Workforce Development

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Program Managers / Mission Owners

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Contracting & Procurement Officers

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Agency CISO / Security & Compliance

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Privacy Officers, General Counsel, IG

## What We Do (Scope at a Glance)

### Systems & Data Mapping

Inventory: HRIS (e.g., USA Staffing, DCPDS, Workday Government), LMS (Cornerstone for Government, Percipio, FedVTE, AgLearn), Case Management (ServiceNow Gov, Salesforce Government Cloud), ERP/Finance (SAP S/4HANA Public Sector, Oracle Federal Financials), Identity (PIV/CAC via Entra/Okta for Government), Storage (GovCloud S3/DISA/SharePoint Gov).

Schemas & Contracts: personnel records, training completions, certifications, clearance levels, compliance status, regulatory metadata. Policy & Governance: classification fields, need-to-know scopes, retention schedules, redaction maps, authorization flows.

### MCP Server Development

We build production-grade MCP servers for every agency system in your stack. Each server exposes typed tools and resources following the MCP specification, with built-in schema validation, error handling, rate limiting, and observability.

Servers are containerized and deployed via Terraform or Kubernetes manifests you own — in GovCloud, on-prem, or IL4/IL5 enclaves.

### Memory Layer Engineering

MCP-based Connectors: secure adapters that normalize read/write paths across systems. Per-User Memory Graph: knowledge graph + vector index for contextual retrieval (training content, certifications, compliance deadlines, regulatory guidance).

Guardrails Engine: RBAC, field-level permissions, data classification enforcement, need-to-know controls, audit trails. Sync & Freshness: event bus/CDC, backfills, idempotent jobs, conflict resolution, replay.

### Agent Enablement (Optional)

Workforce Coach: citable Q&A grounded in training content, regulations, and agency policies via MCP. Program Assistant: compliance tracking, reporting roll-ups, mandate deadline monitoring, status briefings.

Citizen Service Agent: eligibility lookups, case status, program guidance with provenance. Model Hub: OpenAI, Gemini, Anthropic, Llama, or local/NPU — hot-swappable per policy/cost, air-gap compatible.

### Workflow Automation (Agency Partners)

Proactive nudges (certification renewals, mandate deadlines), case routing, compliance milestones. Content pipelines (ingest → chunk → cite), assessment generation with human review. Approval gates for mission control (human-in-the-loop).

## Deliverables You Keep (No Lock-In)

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MCP server source code for every connected agency system

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Connector code & IaC (Terraform/K8s manifests) to deploy in GovCloud/on-prem/IL4/IL5

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Data dictionaries, MCP tool schemas, and contract tests

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Policy configs (RBAC matrices, classification rules, need-to-know controls, retention/expiry)

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ETL/ELT jobs, sync runbooks, and observability dashboards

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Agent starter kits (prompts, MCP tool definitions, evaluation harnesses)

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Security & Compliance packet (threat model, MCP data flows, NIST 800-53 audit checklist)

## Engagement Model (Hours-Based, Transparent)

### Discovery & Design (1–3 weeks):

workshops, MCP architecture, system inventory, backlog, estimates

### MCP Server Sprints (2–6 weeks):

build and test MCP servers for each agency system, memory layer, policy engine

### Pilot & Hardening (2–4 weeks):

limited directorates or programs, telemetry, MCP performance tuning, handover

### Handoff or Co-Manage:

your team runs it; we stay on a light retainer if desired

### Billing:

hourly, ultra-competitive rates; weekly timesheets; milestone demos; you can pause/rescope anytime

## Security, Privacy, and Compliance

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All MCP servers run in your environment (GovCloud, on-prem, or IL4/IL5 enclaves), with your IAM/KMS

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NIST 800-53 support, NIST 800-53 controls, least-privilege MCP access

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MCP-level data minimization, classification enforcement, need-to-know controls, audit logs

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Red-team prompts, safety filters, and replay evaluation for agents

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mTLS between agents and MCP servers; air-gapped deployment options for sensitive workloads

## Reference Architecture (MCP-Powered)

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MCP Server Layer → Typed connectors to HRIS/LMS/Case-Management/ERP/Identity/Storage

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MCP Gateway → Authentication, rate limiting, request routing, and observability

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Event Bus + CDC → Reliable syncs, backfills, and change capture

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Workforce Memory Layer → Graph + vector store with classification-aware MCP policy retrieval

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Policy/Guardrails Engine → RBAC, data classification, need-to-know enforcement, rate limits

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Agent Interfaces → Coach (workforce), Program Assistant (manager), Citizen Service Agent (public)

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Observability → MCP request traces, latency metrics, cost monitors, evaluation harnesses

## Common Use Cases We Deliver

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"Single pane of glass" coach with training history, certifications, and clearance context — powered by MCP connections to HRIS, LMS, and personnel systems

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Program assistant that tracks compliance mandates and triages reporting questions (cited answers from MCP-connected regulatory materials)

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Citizen service agent that surfaces eligibility and case status with provenance via MCP queries across program, identity, and case management systems

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Cross-system automations: certification-renewal triggers, mandate deadline alerts, onboarding workflows — orchestrated through MCP tool chains

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Regulatory content ingestion pipelines with citations and classification safeguards

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Multi-agent workflows where specialized agents collaborate through shared MCP servers — one agent handles workforce development, another handles compliance, a third handles citizen services — all sharing the same secure data layer

## Why ibl.ai FDEs

### MCP-native architecture:

every integration we build follows the open MCP standard — no proprietary lock-in

### Government native:

NIST 800-53 controls, PIV/CAC authentication, GovCloud/IL4/IL5 deployment readiness baked in

### Ownership by design:

you get the MCP server code, configs, and deployment scripts

### Model-agnostic and cost-aware:

MCP works with any LLM provider including air-gapped models; swap and optimize freely

### Speed + rigor:

we ship working MCP integrations quickly, with tests and runbooks

## Get Started

### Architecture Review (hours):

map systems, goals, risks, and design your MCP server topology

### Fixed-Scope Pilot (optional):

cap hours for MCP servers covering a specific program or directorate

### Ongoing Hours (as needed):

new MCP servers, additional connectors, and workflow builds

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