Pega Data/Integration Engineer (AI)

Job Title: Pega Data/Integration Engineer (AI)

Location: Remote (U.S. based) with occasional travel to client or partner sites as needed

Clearance Requirement: U.S. Citizenship and Green Card Holder with the ability to obtain a clearance

• Ideally US Citizen OR Green Card Holder - A minimum of 3-5 years of continuous U.S. residency is requires due to Federal Background check requirements

POSITION OVERVIEW

Pega Data/Integration Engineer (AI)

Avilamb Inc. is seeking a Pega Data/Integration Engineer (AI) to support a Department of Veterans Affairs (VA) program. This role will focus on secure data integration, AI-enabled services, data governance, and reliable delivery of structured and unstructured data into Pega workflows.

1. Duties and Responsibilities

• 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.

2. Knowledge and Skills Required

• 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.

3. 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.

4. 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.

5. Clearance / Suitability

• Must be able to obtain and maintain a Public Trust clearance

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Thank You

Arnav Acharya

**Recruitment Profes…