• Develop, test and maintain backend applications • Write clean, efficient, and well-documented code • Design and implement data models and database schemas • Collaborate with the frontend team to integrate the backend with the user interface • Perform code reviews and ensure code quality standards are met • Troubleshoot and debug applications • Implement code with very high coverage of unit tests and component tests • Cross-training peers and mentoring teammates • Work with the DevOps team to deploy and manage applications in production • Continuously learn and stay up-to-date with new technologies and industry trends

• Design and implement multi-step, agentic AI workflows (planner/executor, tool-using agents, RAG + memory patterns) • Engineer robust contextual pipelines including: • Retrieval-augmented generation (RAG) • Structured memory (short-term, long-term, episodic) • Tool invocation and function calling • Control hallucination, drift, and overreach through grounding, validation, policy constraints, and ensemble methods. • Optimize context windows, token usage, and latency under federal cost, platform quotas, and performance constraints. • Build production-grade services using Python, Java, C++, Rust, GO, C#, TypeScript • Implement APIs and microservices that integrate AI agents with: • Data lake house • SharePoint • Microsoft Graph API • Line-of-business systems • Apply secure coding practices aligned with NIST 800-53 / 800-171 • Design and deploy solutions in GCCH environments • Work within constraints such as: • Limited model availability • Restricted outbound network access • Controlled identity and authentication flows • Use Azure services including: • Azure AI (OpenAI / Foundry where applicable) • Azure Kubernetes Service (AKS) • Azure Functions / App Services • Azure Data Lake Storage • Azure Key Vault • Implement identity, RBAC, and managed identities aligned with federal requirements • Design AI systems with auditability, traceability, and explainability • Support Authority to Operate (ATO) processes • Implement logging, monitoring, and human-in-the-loop controls • Ensure data residency, data minimization, and model usage compliance

• Design, build, and evolve a large-scale Optimizely DXP implementation • Collaborate closely with team members across various functions • Optimize site performance and compliance • Mentor and provide technical leadership to engineers • Develop infrastructural solutions and manage hosting environments

• Develop and enhance ServiceNow applications, workflows, UI policies, business rules, integrations, and custom components following platform best practices. • Build and maintain ServiceNow Portal components (Angular/Seismic) where applicable. • Create scalable, maintainable technical solutions to solve complex business problems. • Configure and extend modules such as ITSM, CMDB, Asset, App Engine, and custom scoped applications. • Design, implement, and optimize data models, forms, ACLs, client/server scripts, UI actions, and Flow Designer automations. • Investigate, triage, and resolve client and operational issues, performing root cause analysis and implementing long-term solutions. • Maintain detailed documentation of configurations, development work, and system behaviors. • Work directly with clients, product managers, operations, and project management to define requirements and ensure timely delivery of solutions. • Participate in Agile ceremonies, sprint planning, code reviews, and knowledge sharing within the engineering team.