Data and Agentic AI Platform Engineer (Remote)

Prospect Engage; Northern (KY); Remote; USD 85,000 - 110,000; Full time

Benefits offered by this job

Paid time off

Paid holidays

401k retirement contributions

Health insurance

100% remote work

Job summary

ProspectEngage, LLC is hiring a data/platform engineer for a 100% remote role within the United States. You will strengthen the data foundation, build ingestion pipelines, and develop AI-enabled features across PostgreSQL, Dataverse, and microservices.

Collaboration with the Director and Platform Development Specialist is essential. The role emphasizes building secure, auditable AI workflows, robust APIs, and reliable data-quality controls.

Qualifications

• 3+ years in data engineering or platform engineering.
• Experience with relational data modeling and ETL pipelines.
• Strong SQL and data quality practices.
• Ability to design scalable APIs and backend systems.

Responsibilities

• Design and improve relational data models across PostgreSQL and Dataverse.
• Build ingestion and synchronization workflows for data entities.
• Develop Python/FastAPI services and REST APIs.
• Create private AI workflows with proper approvals and access controls.
• Collaborate with cross-functional teams and document decisions.

Skills

PostgreSQL

Python

FastAPI

Data modeling

ETL/ELT pipelines

API design

CI/CD

OAuth 2.0

AI integration

Tools

Dataverse

React

Git/GitHub

Microsoft Dynamics 365

OAuth 2.0

Job description

Build the Future of Economic Development.

Help us turn data, software, and AI into practical tools that support economic development organizations and the communities they serve.

Work arrangement 100% remote within the United States

Compensation $85,000–$110,000, depending on experience

Level Mid-level; exceptional early-career candidates may be considered

Reports to Director of ProspectEngage; works closely with the Platform Development Specialist

About ProspectEngage®

ProspectEngage®, LLC, is an economic development technology and business intelligence company. We provide software, data, artificial intelligence, and digital tools designed for economic development organizations and government agencies.

Our core product, ProspectEngage® CRM, is a purpose-built relationship and business intelligence platform supporting business attraction, business retention and expansion (BR&E), project and investment tracking, company research, communications, performance measurement, and digital prospect intelligence. We are building toward a secure, agentic operating platform in which governed internal and external data can support specialized AI agents that research, monitor, analyze, recommend, and—with appropriate approvals—take action.

The Opportunity

This role will help strengthen the data and application foundation of ProspectEngage® and turn emerging AI capabilities into dependable product features. You will work across PostgreSQL, Microsoft Dynamics 365/Dataverse, backend services, APIs, React interfaces, workflow automation, and AI-agent infrastructure.

The immediate priorities are improving database quality and maintainability; creating reliable ingestion, enrichment, matching, and synchronization pipelines; and developing a private, auditable AI layer that allows agents to use authorized company, contact, project, activity, and market-intelligence data safely. This is a hands-on engineering role—not a prompt-writing-only position.

What You Will Own and Contribute To

Design and improve relational data models across PostgreSQL and Dataverse, including entities, relationships, constraints, indexes, migrations, and lifecycle rules.

• Build repeatable ingestion, transformation, enrichment, entity-resolution, deduplication, and synchronization workflows for company, contact, project, activity, survey, and market-intelligence data.
• Establish practical data-quality controls, validation rules, provenance, lineage, audit logs, rollback paths, and exception-review workflows.
• Develop and maintain Python/FastAPI services, REST APIs, webhooks, background jobs, and third-party integrations with strong authentication, error handling, observability, retries, rate-limit handling, and idempotency.
• Build secure agentic AI workflows using structured outputs, retrieval, tool/function calling, workflow state, memory, human approvals, and clear permission boundaries.
• Create evaluation datasets and automated checks for retrieval quality, extraction accuracy, hallucination risk, tool selection, data writeback, cost, latency, and regression testing.
• Implement private knowledge and retrieval services that combine client-authorized data with external intelligence while preserving tenant isolation, access controls, source citations, and data-retention requirements.
• Develop React interfaces for data review, exception handling, approvals, dashboards, configuration, and agent activity/audit trails.
• Integrate ProspectEngage® with Microsoft Dynamics 365/Dataverse, Power Platform, Microsoft 365, and external data providers using OAuth 2.0, OData, REST APIs, and webhooks.
• Contribute to testing, CI/CD, deployment, monitoring, incident troubleshooting, technical documentation, and code review.
• Translate real economic-development workflows into maintainable product requirements and explain technical tradeoffs to non-technical teammates.

Required Capabilities

Data engineering and database management

• Strong SQL and relational data-modeling skills, including joins, constraints, indexing, query tuning, transactions, schema migrations, and debugging data integrity issues.
• Experience building or maintaining ETL/ELT or API-based pipelines, with practical approaches to deduplication, entity matching, data validation, provenance, and reconciliation.
• A disciplined approach to production data changes: staging, backups or rollback plans, idempotent operations, auditability, and readback verification.

Python, APIs, and backend systems

• Strong Python fundamentals and experience working in an existing production codebase.
• Experience building or maintaining REST APIs; FastAPI or a similar framework is strongly preferred.
• Working knowledge of authentication and authorization, OAuth 2.0, JSON, webhooks, pagination, rate limits, asynchronous work, background jobs, logging, and error handling.

Applied AI and agentic systems

• Hands-on experience integrating LLM APIs into software using structured outputs and tool/function calling.
• Understanding of retrieval-augmented generation (RAG), embeddings or hybrid search, chunking and metadata strategies, workflow state, agent memory, and model/provider abstraction.
• Ability to design human-in-the-loop approvals, guardrails, permissions, citations, evaluation harnesses, and monitoring for agent behavior.
• Ability to identify and mitigate prompt injection, data leakage, over-permissioned tools, hallucinated actions, and unsafe or unverified writebacks.

Software delivery and troubleshooting

• Working experience with Git/GitHub, pull requests, code review, automated testing, environment management, and basic Linux/cloud operations.
• Ability to trace failures across frontend, backend, database, authentication, external APIs, configuration, and infrastructure.
• Comfort using AI coding tools such as Codex, Claude, or similar systems while independently reviewing, testing, and taking responsibility for the resulting code.

Communication and product judgment

• Ability to turn ambiguous operational needs into scoped technical requirements and incremental releases.
• Clear written documentation and the ability to explain decisions, risks, and tradeoffs to technical and non-technical colleagues.
• Curiosity, independence, and sound judgment about when automation should act, when it should ask for approval, and when it should stop.

Preferred Experience

• Microsoft Dynamics 365/Dataverse, including tables, lookups, custom fields, OData/Web API, app registrations, security roles, and solution-aware development.
• Microsoft Power Platform, Microsoft Graph, Power Automate, or Power Apps.
• PostgreSQL extensions or search technologies such as pgvector, full-text search, hybrid retrieval, or a comparable vector/search platform.
• Multi-tenant SaaS architecture, role-based access control, secrets management, encryption, privacy, and secure handling of client or government data.
• Containers, cloud hosting, CI/CD, queues or schedulers, application monitoring, and deployment troubleshooting.
• CRM systems, master data management, business intelligence, data enrichment, or economic development workflows.

What Success Looks Like in the First 6-12 Months

• A documented, prioritized data-model and data-quality improvement plan is in active implementation.
• Core ingestion and synchronization workflows are observable, restartable, auditable, and substantially easier to troubleshoot.
• Duplicate, incomplete, stale, and conflicting records are measured and handled through clear automated and human-review rules.
• At least one production agent workflow retrieves authorized data, cites its sources, uses tools safely, passes defined evaluations, and records an auditable activity trail.
• Data or CRM writebacks use approval gates, conflict checks, idempotency, and readback verification rather than unreviewed autonomous updates.
• The team has reusable testing, evaluation, deployment, and documentation patterns that reduce risk as new agents and integrations are added.

Qualifications

We expect the strongest candidates to have approximately 3+ years of relevant software, data, or platform engineering experience, or an equivalent portfolio demonstrating production-quality work. A specific degree is not required. You do not need to be an expert in every technology on day one, but you must have strong fundamentals, learn quickly, and be able to own work through design, implementation, testing, deployment, and documentation.

We especially value candidates who can show a real system they built or improved, explain its data model and failure modes, describe how they validated AI-generated or externally sourced data, and discuss how they protected production data during changes.

Compensation and Benefits

Compensation is expected to range from $85,000 to $110,000 depending on experience. ProspectEngage® offers paid time off, paid holidays, a paid week off at the end of the year, 401k retirement plan contributions, health insurance, and the flexibility of 100% remote work.

Application Process

Applicants must be authorized to work in the United States. We are unable to sponsor employment visas.

ProspectEngage® is an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by applicable law.