• Work with onsite lead/client teams to understand the scope and deliverables for custom application development or Extensions using Apex and VBCS • Perform requirements analysis, design, develop, test and deploy custom applications and extensions • Experience in designing the Database structure, process flows, exception handling and reporting for Custom applications • Maintain documentation on all work products as per Company standards • Develop Workflow as per business requirements using Apex • Develop the Reports as per business requirements using Apex • Perform administrative tasks including but not limited to set ups, user maintenance, security, single-sign-on • Perform integration requirement analysis, design, develop, test and deployment • Experience in using REST / SOAP APIs for integrations with Cloud ERP and Third party applications

• Lead the technical maturation of advanced prototypes into production-ready systems, identifying gaps in architecture, scalability, reliability, and usability. • Define and drive technical roadmaps that align product features with customer requirements. • Identify and implement variability points to enable rapidly tailoring solutions to the needs of different customers. • Establish criteria for MVPs, beta releases, and production readiness. • Lead planning and implementation of system architectures for AI-enabled software systems, including APIs, services, data pipelines, and deployment infrastructure. • Make informed tradeoffs between research flexibility and product stability, performance, and maintainability. • Guide refactoring of research codebases into modular, reusable, and testable components. • Collaborate with UI/UX designers to understand and incorporate end user interaction needs into architecture decisions. • Design and implement workflows for training, evaluation, deployment, and monitoring of AI/ML models. • Establish MLOps practices including versioning, reproducibility, CI/CD, performance monitoring, and lifecycle management. • Work closely with researchers to transition experimental models into operational pipelines. • Lead containerized deployments using Docker and related tooling; support cloud and on-premise environments. • Apply modern DevSecOps practices to improve system reliability, security, observability, monitoring, logging, and operational diagnostics. • Anticipate operational risks and design mitigations for real-world usage.

• Contribute to real Evoke platform development efforts, including: UI components and frontend features (React/TypeScript) • Backend logic and API integrations • Low-code configuration and workflow design • Support the development and enhancement of platform features, tools, or internal utilities • Participate in team ceremonies such as sprint planning, standups, and retrospectives • Collaborate with engineers to troubleshoot bugs, test functionality, and validate solutions • Assist in building proofs-of-concept or innovation projects (including AI-assisted tools and automation) • Learn and apply modern development practices, including: Version control (Git), Code reviews, Testing strategies, Agile development workflows • Document work and share learnings with peers and the broader team

• Own overall application architecture and drive technical decisions across frontend, backend, simulation, and data tiers • Lead sprint planning, backlog refinement, and technical prioritization in coordination with project leadership • Conduct code reviews and enforce standards for code quality, testing, documentation, and maintainability • Serve as a primary technical point of contact for Government engineering and product stakeholders • Translate Government requirements and mission context into actionable engineering tasks and solution designs • Modernize and extend a Python FastAPI backend serving as the application control plane for data operations, scenario lifecycle management, and AI orchestration • Decouple the SimPy discrete-event simulation engine from the API tier into independently scalable worker containers • Design and implement run request queueing, worker orchestration, and result persistence patterns • Build governed ingestion workflows, including validation services for schema enforcement, referential integrity, circular reference detection, and business-rule validation with actionable user-facing feedback • Implement dataset versioning, lineage tracking, and run-level traceability linking scenario outputs to explicit input versions • Extend and maintain a React / TypeScript frontend using Material UI, Recharts, and data-grid-based visualizations • Design and implement the AI integration layer brokering access between the application backend and a Government-approved hosted LLM endpoint • Instrument the application pipeline to capture timing, bottleneck, concurrency, and throughput metrics • Design and execute integration testing across frontend, backend, database, object storage, cache, and worker services.