eSimplicity

• Provide executive accountability for program performance, strategic alignment, contract and budget governance, stakeholder escalation, and overall delivery health. • Lead an integrated, multi-team delivery model that maintains coverage across platform foundations, cloud operations, security, data supply chain, metadata, governed data asset operations, analytics experience, dashboard governance, public-facing products, AI and advanced platform enablement, external exchange, APIs, partner integrations, user success, documentation, and change management. • Maintain a highly collaborative operating model that gives customer personnel continuous visibility into code, documentation, backlogs, metrics, dashboards, risks, decisions, and operational status in approved systems of record. • Oversee program deliverables and management artifacts, including roadmap and PI Planning packages, monthly status, risk, and performance reporting, quality inputs, staffing and retention information, transition-in and transition-out readiness, and continuity planning. • Provide leadership over applicable coverage areas, including cross-cutting program leadership, architecture coordination, product management, engineering operations, data operations, support operations, domain expertise, and enterprise stakeholder engagement. • Promote reuse, portability, documentation quality, customer ownership of artifacts, and sustainable operations across code, infrastructure, analytics products, runbooks, AI configurations, metadata, service guides, and transition materials. • Serve as the primary interface to client leadership, product owners, and security stakeholders, cloud and platform partners, product teams, and directed policy or operations groups owning stakeholder escalation and maintaining a collaborative, responsive, and trusting relationship. • Collaborate with government partners on the strategic direction of the program, confirming alignment with agency data strategy imperatives and measurable progress toward program goals. • Ensure program management practices make outcomes measurable across service reliability, data quality, delivery flow, engineering health, security and compliance, user success, analytics adoption, cost transparency, AI services, AIOps, and metadata maturity. • Foster a badge-less culture of innovation and continuous improvement, driving cross-functional team success and coordinating across related programs and platform teams.

• Own roadmap development, intake-to-prioritization governance, user and stakeholder alignment, value measurement, and sequencing of cross-team product work. • Develop and maintain thematic roadmaps that communicate how the program will deliver value in short-term and longer-term increments while remaining adaptable to funding, statutory, security, source-readiness, and policy changes. • Partner with customer product owners and management stakeholders to define expected outcomes, hypotheses, value measures, trade-offs, and success criteria for features, workflows, data products, dashboards, APIs, and AI capabilities. • Use user archetypes, journey research, support trends, and qualitative and quantitative feedback to guide product strategy, onboarding, documentation, service design, and AI rollout decisions. • Coordinate product sequencing across delivery workstreams, including user success, documentation, support, analytics experience, dashboard governance, public-facing products, AI and platform feature enablement, data supply chain, metadata maturity, APIs, and partner integrations. • Promote simple, intuitive, accessible user experiences across onboarding, access, discoverability, documentation, dashboards, conversational analytics, public-facing products, and support escalation paths. • Lead applicable coverage areas, including unified front-door service, user support, onboarding, documentation, coaching and training, communications, analytics discoverability, dashboard governance, AI service rollout, support operations, and stakeholder engagement.

• Lead engineering operations standards, CI/CD and release governance, SLO/SLI framework development, operational readiness criteria, DevSecOps practices, and reliability across the delivery model. • Provide leadership for applicable technical coverage areas, including cloud infrastructure, infrastructure as code, CI/CD, source control, identity and access, observability, security automation, API runtime operations, security assessment support, remediation tracking, access reviews, vulnerability response, FedRAMP or comparable security alignment, and support escalation practices. • Implement DevSecOps principles across the lifecycle, including iterative delivery, continuous integration and deployment, security shifted left, security by design, automated security testing, continuous monitoring, cross-functional collaboration, and continuous improvement. • Establish and maintain release readiness and completion criteria for platform, infrastructure, pipeline, API, dashboard, documentation, AI-enabled service, and security artifact work. • Support automated testing expectations, including CI/CD-integrated unit, lint, smoke, functional, performance, accessibility, and security tests, with a target of at least 80 percent automated test coverage for code-based deliverables unless the customer approves an alternative. • Drive observability and operational action paths for service health, incident trends, performance, deployment risk, platform reliability, security posture, support escalation, and runbook-based recovery. • Coordinate with customer stakeholders and cloud or platform partners on cloud governance, architecture reviews, account governance, logging, backups, patching, vulnerability scanning, cost management, and approved cloud service use. • Ensure engineering artifacts, code repositories, infrastructure-as-code modules, runbooks, dashboard definitions, CI/CD workflows, security evidence, and related materials are maintained in customer-accessible systems of record from day one.

• Own reference architecture, cross-team technical standards, architecture governance and decision-making, interoperability patterns, and major technical trade-off analysis. • Lead applicable technical coverage across cloud and DevSecOps engineering, data engineering, data governance and metadata specialization, BI and analytics development, AI/ML platform engineering, security engineering and compliance, API services, partner integrations, and domain architecture. • Guide architecture for platform-first delivery, approved technology direction, infrastructure as code, governed data trust patterns, API-first reuse, secure data sharing, AI-enabled service patterns, public-facing dashboards, and transition-ready artifact management. • Coordinate with customer stakeholders, cloud and platform partners, security and privacy stakeholders, data owners, product teams, and downstream consumers on architecture reviews, environment changes, source onboarding, integrations, public-facing releases, and major technical decisions. • Develop and maintain architectural artifacts in customer-accessible systems, including reference architectures, decision records, diagrams, standards, runbooks, interface documentation, joint operating agreements, service guides, data-flow documentation, and transition materials. • Evaluate new or materially changed services against security, privacy, accessibility, cost transparency, observability, operational readiness, metadata maturity, AI governance, portability, and reuse criteria. • Support joint operating agreements and cross-platform coordination for source-system and downstream-system interfaces, ingestion lead times, schema and metadata changes, incident boundaries, release dependencies, security and privacy responsibilities, support handoffs, and transition responsibilities. • Promote out-of-the-box, native, reusable, open-source-aware, and portable solutions while minimizing unnecessary proprietary dependencies and avoiding contractor-managed external data systems.

• Lead data strategy execution, data supply chain and metadata maturity leadership • Oversee data platform operations, distributed processing, programming and query languages • Operate and improve source onboarding, ingestion, transformation, data quality • Advance the program’s data trust model • Establish and monitor data quality and processing timeliness practices • Coordinate with data owners and teams • Ensure metadata maturity advances as a tracked, multi-year effort • Support governed self-service analytics, certified dashboards, and secure data sharing

• Lead the scaled agile delivery model across the program, including PI Planning coordination, cross-team cadence management, dependency and risk tracking, and delivery transparency to the customer. • Ensure all teams can participate fully in agile practices, including two-week sprint delivery, quarterly Program Increment planning, backlog refinement, sprint planning, daily coordination, demos, retrospectives, and cross-team coordination forums. • Coordinate with product, architecture, engineering, data, security, AI, analytics, and user success leaders to align team backlogs with PI objectives, roadmap priorities, delivery constraints, and customer decision needs. • Maintain visibility into delivery flow, program risks, dependencies, impediments, decisions, and delivery health using customer-approved work management, documentation, collaboration, source control, and dashboarding tools. • Support routine reporting of delivery and product metrics, including deployment frequency, lead time to change, mean time to restore, change failure rate, burndown, sprint performance, PI performance, velocity, deliverable timeliness, and deliverable quality. • Facilitate regular demonstrations of working software, operational improvements, research findings, documentation improvements, dashboards, APIs, AI capabilities, and other demonstrable progress. • Promote blameless retrospectives and continuous improvement across delivery quality, service quality, collaboration, supportability, operational resilience, testing, and release readiness. • Lead agile coordination for applicable coverage areas, including cross-cutting program leadership, product management, engineering operations, architecture coordination, data operations, user success, support operations, and participation across all delivery workstreams.

• Lead data science work across structured and unstructured program data, including data collection, processing, cleaning, profiling, and preparation for analysis and modeling on a governed data platform. • Design, develop, train, evaluate, and refine machine learning models and AI services, selecting appropriate algorithms and techniques for specific customer and mission needs. • Support deployment, monitoring, and maintenance of model performance in cloud environments using model lifecycle management, model serving, vector search, model evaluation, and related MLOps tooling. • Deliver capabilities across both program AI tracks: internal AI-enabled delivery acceleration (AI-assisted schema tagging, automated code review, documentation generation, ticket automation) and user-facing AI services for customer users and approved consumers (AI assistants, conversational analytics, document-grounded search, and approved retrieval-augmented generation services). • Operate within the program’s AI governance intake and review process, registering all production and pilot AI use cases before deployment, routing managed endpoints through a governed AI gateway layer, and maintaining inference logging, PII guardrails, rate controls, and human oversight and escalation paths. • Plan and conduct proofs of concept and capability-gate evaluations that assess accuracy, governance integration, cost, operational overhead, and alignment to customer policy before scaling new AI capabilities. • Embed responsible AI and equity requirements into delivery, including algorithmic risk and impact assessments, bias testing across relevant demographic and programmatic subgroups, plain-language limitations and escalation paths, and periodic bias and drift re-review. • Collaborate closely with ML engineers, data engineers, platform teams, and cross-functional partners to develop and maintain the infrastructure and governed cloud environment required for AI/ML operations. • Create, maintain, and improve documentation for methodologies, code, assumptions, experiments, evaluation artifacts, and decisions, including documentation of AI tools within the software bill of materials (SBOM), to support reproducibility and governance review. • Communicate technical findings, strategic vision, risks, tradeoffs, and business value to leadership and key stakeholders, and provide people-management support and day-to-day technical guidance to a team of 3–5 engineers.

• Partner with the development team to implement secure engineering patterns, maintain secure CI/CD pipelines, and remediate vulnerabilities, including contributing code, configuration, pipeline changes, and infrastructure updates where appropriate. • Design and maintain security gates for code quality, dependency scanning, container image scanning, secrets detection, infrastructure misconfiguration, and policy compliance. • Support Kubernetes and container security for AWS EKS environments, including image hardening, admission controls, runtime monitoring, network policies, workload identity, secrets management, and least-privilege access patterns. • Support controls for new tooling/integration usage, the handling of sensitive data, and access controls. • Help define and enforce secure-by-default engineering standards across the application, infrastructure, and delivery pipeline. • Help drive the move toward ATO and near-real-time compliance. • Implement monitoring of production runtime environments for vulnerabilities and compliance drift and make security and compliance reporting available on demand. • Translate security findings into actionable engineering work items in JIRA and support teams through remediation, validation, and closure. • Identify, document, and communicate security risks tied to modernization efforts • Monitor cloud environments using AWS tools • Participates in Agile processes including daily standups, demos, retrospectives, and sprint planning • Collaborates with a fully integrated Agile team to deliver continuous improvement to designs, processes, and standards

Role Description The Java Developer is responsible for designing, developing, testing, and maintaining scalable software applications using Java technologies. This role supports enterprise systems and mission-critical applications by translating business and technical requirements into reliable, secure, and high-performance solutions. The position works closely with architects, business analysts, DevOps engineers, and quality assurance teams to deliver software solutions that align with organizational standards and best practices. The ideal candidate has strong foundational to intermediate Java development experience and contributes across the full software development lifecycle, including: - Design, develop, test, and maintain Java-based applications and services. - Write clean, efficient, and well-documented code following industry best practices. - Participate in requirements analysis and technical design discussions. - Develop RESTful APIs and backend services. - Integrate applications with databases, third-party systems, and cloud services. - Support application deployment, configuration, and troubleshooting. - Participate in code reviews and ensure adherence to coding standards. - Collaborate with cross-functional teams in Agile or Scrum environments. - Create and maintain technical documentation. - Troubleshoot and resolve defects and performance issues. - Ensure compliance with security, data protection, and coding standards. Qualifications - Working knowledge of Java (Java 8 or higher preferred). - Understanding of object-oriented programming (OOP) principles. - Familiarity with common Java frameworks (e.g., Spring or Spring Boot). - Basic knowledge of RESTful web services and API development. - Understanding of relational databases (e.g., SQL, PostgreSQL, MySQL). - Knowledge of version control systems such as Git. - Familiarity with build tools such as Maven or Gradle. - Basic understanding of software development lifecycle (SDLC) methodologies. - Ability to develop and debug Java applications. - Strong analytical and problem-solving skills. - Ability to write efficient SQL queries. - Effective written and verbal communication skills. - Ability to translate business requirements into technical solutions. - Ability to work in Agile development environments. - Ability to work independently and as part of a collaborative team. - Ability to manage multiple tasks and deadlines. - Ability to learn new frameworks, tools, and technologies quickly. - Ability to maintain confidentiality and adhere to secure coding practices. - Ability to provide technical support and knowledge transfer when required. Requirements - All candidates must pass public trust clearance through the U.S. Federal Government. - Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field. - 4+ years of experience in Java development. - Experience with Spring Framework / Spring Boot. - Experience with RESTful API development. - Experience with JPA / Hibernate. - Experience with CI/CD pipelines and DevOps tools (e.g., Jenkins, GitLab CI). - Experience working in Agile/Scrum environments. Benefits - Comprehensive benefits package, including medical, dental, and vision coverage. - 401(k) retirement benefits. - Paid time off and paid holidays. - Life and disability insurance. - Additional wellness and employee support programs.

• Define the product or team's vision within the scope of a particular team, product or feature set, ensuring alignment with user needs and business objectives • Develop a clear perspective on future goals and definitions of success for the team/product and actively contribute to developing the long-term product vision and approach • Develop expertise in the policies, operations, and targeted outcomes enabled by the team's work; Build a deep understanding of user needs, behaviors, and pain points that guide product strategy and decision-making • Interface with Federal customers, end users, and Human-centered Design (HCD) researchers to identify and validate user and business needs • Understand the scope of the enabler work and collaborate with System Architects, SMEs, Engineers, and others to assist with product planning and decision-making • Understand, visualize, and manage upstream/downstream dependencies • Prepare for and Participate in Quarterly (PI) Planning • Support and lead Agile ceremonies (including planning, refinement, retrospectives, and standups) • Develop actionable and value-driven features and stories, working with the team to define benefit hypothesis and acceptance criteria • Collaborate with the development and testing team to ensure the implementation of the system tests • Provide operational, tactical, and strategic inputs to accomplish program goals, meet planned deliverables, and exceed user satisfaction • Drive delivery and continuous improvement by utilizing feedback and metrics to identify areas of opportunity • Provide proactive and open communication across the program and stakeholders for transparency and awareness of progress and impediments • Bridges the communication between the agile/project teams and key stakeholders by building and maintaining relationships.