Jobs at Groundswell

Lead infrastructure and platform engineering teams, oversee capacity, schedules, risks, governance, and delivery quality. Design secure, scalable AWS architectures and external integrations; translate business needs into technical roadmaps and implementation plans. Establish standards for data integration, configuration, compliance, and auditability. Guide Agentic Audit technology evolution, evaluate emerging technologies, conduct technical and code reviews, and support platform deployments in a DevSecOps environment.

Designs and leads scalable data architectures for enterprise applications built on Appian. Responsibilities include data modeling, relational database design, SQL optimization, integrations, data governance, security, performance troubleshooting, and technical reviews. Collaborates with architects, developers, federal stakeholders, and client leadership while mentoring technical teams and translating business requirements into secure, maintainable data solutions.

Build and operate secure batch and streaming data pipelines across structured, semi-structured, and legacy sources. Responsibilities include data ingestion, integration, quality validation, governance, monitoring, alerting, workflow orchestration, deployment automation, troubleshooting, and provenance management. Collaborate with engineering, cloud, data science, security, architecture, and customer teams to deliver reliable data products and AI-enabled workflows in regulated environments.

Build and operationalize production AI solutions for federal clients, from stakeholder discovery and architecture through evaluation, deployment, governance, monitoring, and optimization. Develop LLM applications using retrieval, structured outputs, tool use, and agentic workflows. Define quality metrics, create evaluation sets, document limitations, advise clients on AI use cases, and mentor engineers while contributing to reusable internal patterns and products.

Owns AI capabilities end to end, from stakeholder discovery and technical design through development, evaluation, deployment, monitoring, and documentation. Builds LLM applications using retrieval, structured extraction, tool use, and agent patterns; defines measurable quality criteria; balances accuracy, cost, latency, security, and complexity; supports client delivery and proofs of concept; and mentors engineers new to AI.

Build production-quality AI applications for federal clients and internal products. Responsibilities include gathering requirements, designing prompts and retrieval workflows, integrating APIs and data, creating evaluations, investigating failures, documenting limitations, and supporting proofs of concept and client demonstrations. The role requires client-facing communication, comfort with ambiguity, and the ability to translate business needs into working software.

Build and operate AI-assisted data platforms using data preparation, knowledge graphs, semantic technologies, machine learning, and AI agents. Profile and reconcile enterprise data, create metadata and evaluation sets, assess language-model workflows, analyze human-review feedback, and improve platform performance. Partner with engineering teams to deploy validated solutions, maintain reproducible documentation, and communicate findings to technical and mission stakeholders. Handle sensitive data under governance and audit controls while supporting solution planning and proposals.

Leads technical delivery for a complex Workday implementation supporting an Intelligence Community customer. Coordinates integration, data conversion, security, environments, testing, deployment, and cross-workstream dependencies. Partners with delivery, architecture, CIO, cybersecurity, vendor, and program teams to manage technical risks, milestones, readiness, and mitigation strategies. Supports design reviews, cutover, operational transition, and concurrent contract coordination while translating technical issues into clear program impacts and decisions.

Designs and operates secure batch and streaming data pipelines across cloud platforms. Responsibilities include data ingestion, integration, modeling, quality validation, governance, lineage, security, monitoring, workflow orchestration, and performance optimization. The role supports analytics, machine learning, AI-enabled applications, and authoritative data services while documenting architectures, runbooks, and data contracts. Collaboration with engineering, cloud, security, data science, architecture, and customer teams is required, along with contributions to secure data platform proposals.

Designs, deploys, and operates secure, scalable AWS infrastructure and application services for mission-focused platforms. Builds Kubernetes-based containerized services, Infrastructure as Code, CI/CD pipelines, integrations, security controls, observability, and operational documentation. Troubleshoots distributed systems, supports compliance-oriented environments, and collaborates with architects, developers, security teams, data specialists, and customers. Requires a bachelor’s degree, four years of relevant experience, U.S. citizenship, and the ability to obtain and maintain a Public Trust Clearance.

Supports Talent Acquisition through interview scheduling, candidate verification, recruiting system audits, referrals, sourcing, candidate communications, documentation, reporting, and data integrity. The role coordinates onsite interviews, maintains recruiting records in compliance with OFCCP requirements, updates process resources, and supports recruiting projects while handling confidential information and multiple priorities.

Leads a team of test specialists and owns system, regression, performance, integration, acceptance, end-to-end, and automated testing programs. Develops test strategies, translates requirements into test objectives, builds UiPath automation, analyzes defects and test results, and provides recommendations to government stakeholders. Requires Agile experience, test leadership, 5+ years of software testing experience, relevant certification, and an IT-II Non-Critical Sensitive clearance.

Supports an Agile software development team by eliciting, documenting, validating, and managing business and technical requirements. Creates user stories, process flows, use cases, acceptance criteria, and traceability artifacts; coordinates stakeholder reviews and sign-off; evaluates change impacts; and supports testing, implementation, troubleshooting, helpdesk support, and technology modernization initiatives. Uses Jira and Atlassian tools to track requirements, defects, tasks, and project information while reporting risks, issues, and status to the Project Manager.

Designs scalable Databricks solutions and ETL/ELT pipelines while administering MariaDB and SQL Server environments. Responsibilities include database design, performance tuning, backup and disaster recovery, security and access management, data modeling, quality and lineage, and troubleshooting complex data issues. The role collaborates with stakeholders and technical teams, translates requirements into secure solutions, provides technical direction, and delivers demonstrations and training for Department of Transportation support.

Configure and develop Collibra governance, metadata, cataloging, glossary, workflow, and lineage solutions. Integrate Collibra with Databricks and enterprise data sources using REST APIs, Edge, scripting, and integration frameworks. Support data quality, stewardship, testing, deployments, security configuration, upgrades, troubleshooting, reporting, and production operations. Collaborate with governance, engineering, architecture, business, and data stewardship teams in an Agile environment.

Partner with Appian product teams to elicit and document requirements, design BPM/data models and UI, author Agile user stories, run discovery workshops, support MVP and roadmap planning, refine backlog, estimate and accept stories, track risks, and recommend process improvements.

Lead the architecture and delivery of enterprise Workday HCM solutions for federal clients. Responsibilities include translating requirements into scalable and secure designs, leading cross-functional delivery teams, overseeing implementations, reviewing and optimizing applications, managing risks, producing technical documentation and estimates, supporting sales discussions, and delivering demonstrations and training. The role requires Workday expertise, enterprise architecture knowledge, client engagement, team leadership, and collaboration with product, engineering, cloud, and security teams.

Leads day-to-day execution of a complex federal Intelligence Community modernization program. Responsibilities include contract compliance, deliverables, QASP performance, integrated scheduling, risk and dependency management, financial forecasting, invoicing, customer governance, subcontractor oversight, and coordination with OEM and government stakeholders. The role supervises workstream leaders, supports executive program leadership, manages program health and escalations, and assumes increasing leadership responsibility through implementation and steady-state operations.

Leads the end-to-end data conversion workstream for complex Workday implementations. Responsibilities include conversion strategy, extraction, mapping, cleansing, transformation, validation, reconciliation, data loads, documentation, risk management, and coordination with configuration, integration, testing, security, technology partners, and client stakeholders across secure environments.

Leads the integration workstream for a complex Workday implementation supporting a federal Intelligence Community customer. Responsibilities include developing integration strategy, designing and building Workday and enterprise-system integrations, coordinating testing and deployment across secure environments, resolving defects, managing risks and dependencies, maintaining technical documentation, and leading employee and subcontractor integration teams.