> Markdown version of [/jobs/ext/3077892-pega-data-integration-engineer-ai](https://www.wearedevelopers.com/jobs/ext/3077892-pega-data-integration-engineer-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Pega Data/Integration Engineer (AI)

- **Company:** Technatomy Corporation
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, User Authentication, Cloud Computing, Information Systems, Computer Programming, Content Analysis, Data Cleansing, Information Engineering, Extract Transform Load (ETL), Data Mapping, Monitoring of Systems, JSON, Python (Programming Language), Metadata, Zero Trust Network Access, Search Technologies, SQL Databases, Data Streaming, Unstructured Data, Management of Software Versions, Pega, Data Logging, Data Processing, Scripting, Enterprise Software Applications, Retrieval-Augmented Generation, Large Language Models, AI Platforms, Information Technology, Low Latency, Pure Data, Enterprise Integration, Api Design, Restful APIs, Data Pipelines
- **Published:** September 25, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9194225/pega-dataintegration-engineer-ai

## About the Role

We are seeking an experienced Pega Data / Integration Engineer with AI-enablement experience to build governed data and service integrations supporting anomaly detection, predictive analytics, intelligent workflow, and configurable report generation for an enterprise Department of Veterans Affairs solution. This is an engineering and integration role-not a pure data-science position-and is suited to candidates who can connect approved AI services to secure, traceable enterprise data and Pega workflows., · 5+ years of experience in data engineering, enterprise integration, API development, analytics engineering, or comparable technical roles.

· Hands-on experience integrating AI/ML, NLP, analytics, or model-based services into an enterprise application or workflow; extensive model-training research experience is not required.

· Strong knowledge of REST APIs, JSON, authentication, data mapping, error handling, logging, and secure service integration.

· Experience with SQL and at least one programming or scripting language commonly used for data or integration work, such as Java or Python.

· Experience with ETL/ELT, data pipelines, data quality, metadata, lineage, reconciliation, and structured or unstructured data processing.

· Understanding of human-in-the-loop AI, explainability, versioning, monitoring, auditability, and responsible data handling.

· Ability to work with architects, data scientists or vendors, developers, security teams, testers, and business SMEs.

· Strong analytical, troubleshooting, documentation, and communication skills.

KNOWLEDGE AND SKILLS DESIRED:

· Experience with Pega data/integration capabilities, Pega Process AI, Pega GenAI, or another workflow platform's AI services.

· Familiarity with retrieval-augmented generation, vector search, document extraction, model endpoints, or cloud AI services.

· Experience in Federal, financial, acquisition, health, or another regulated environment; direct VA experience is not required.

· Working knowledge of FedRAMP, Zero Trust, privacy, ethical AI, bias testing, model monitoring, or AI governance.

· Relevant Pega, cloud, data engineering, integration, or AI certification is preferred, but not required.

EDUCATION:

· Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, or a related discipline, or an equivalent combination of education and experience.

CLEARANCE:

· Must be able to obtain and maintain a Public Trust clearance.

## Description

· Design and implement data pipelines, services, and integration patterns that support Pega workflows, AI-assisted reporting, anomaly detection, prediction, and document analysis.

· Integrate approved AI/ML, NLP, or large-language-model services through secure APIs or modular connectors without creating unnecessary provider lock-in.

· Prepare and govern structured and unstructured data, including ingestion, normalization, metadata, lineage, quality scoring, source linkage, and access controls.

· Support retrieval, grounding, citation, prompt/input preparation, output parsing, and mapping of AI results into structured Pega data and workflows.

· Develop reusable data features and services for financial variance, execution trends, workflow delays, compliance checks, narrative quality, and related decision-support use cases.

· Implement versioning and auditability for models or services, prompts, templates, input fingerprints, confidence scores, explanations, and user dispositions.

· Collaborate with architects, workflow specialists, business SMEs, security personnel, and testers to maintain human-in-the-loop controls, explainability, privacy, and appropriate use.

· Support test-data preparation and validation of accuracy, bias, drift, false positives/negatives, performance, and operational usefulness before and after release.

· Troubleshoot AI data flows, integration failures, data-quality issues, latency, and output-mapping defects across environments.

· Maintain interface, data, model-integration, configuration, test, and operational documentation in approved repositories.