Aubrant Digital

• Design and build complex, responsive, and accessible user interfaces in Vue 3 using TypeScript, modern JavaScript (ES2020+), HTML5, CSS3, and Sass. • Architect component state, composition, and reusability patterns; write highly optimized, modular components that scale across applications. • Profile and resolve front-end performance bottlenecks across rendering, bundle size, and runtime behavior. • Translate Figma design system outputs into production code, leveraging auto-layout, variables, components, and Dev Mode handoff to maintain fidelity from design to implementation. • Build and maintain reusable UI component libraries and design tokens that codify the design system across products and teams. • Lead implementation of WCAG 2.1 AA compliant interfaces using semantic HTML, ARIA, keyboard navigation, and screen reader testing. • Conduct accessibility audits, define remediation plans, and coach the team on accessibility best practices. • Champion code quality through code review, automated testing, linting, and front-end engineering standards.

• Design and build full test harnesses for .NET solutions, including end-to-end, integration, and API tests using Playwright and complementary frameworks • Maintain and extend existing test suites, refactoring for stability, reusability, and clear failure diagnostics • Partner with developers to make applications testable by design, including hooks, identifiers, and contract patterns • Integrate test execution into Azure DevOps pipelines with appropriate parallelization, reporting, and quality gates • Run and troubleshoot test workloads against Azure-hosted environments, including handling environment-specific configuration • Contribute to release confidence by tying test outcomes to deployment decisions and feedback loops • Pilot and advance agentic automation patterns, AI-assisted test generation, and self-healing test approaches that improve coverage and reduce maintenance • Contribute to QA standards, tooling, and patterns shared across Aubrant engagements • Participate in test planning, defect triage, and quality reviews with engineering and product teams

• Own the technical success of an engagement, ensuring architectural coherence and reuse across services, data, and AI components • Drive technical decisions and document them as ADRs: database engine selection, service vs library boundaries, and integration patterns • Lead architecture review boards and resolve cross-team design dependencies • Set engineering standards: trunk-based development, IaC (Terraform/Bicep), CI gates, SLSA L2 provenance, OpenAPI 3.x and AsyncAPI 2.x contracts, and idempotent integration patterns • Lead code and design reviews; enforce quality gates and SOC 2 control mappings (logical access, monitoring, change management, audit trail) • Plan and orchestrate delivery cadence, including sequencing of build and release windows for engagements with production blackout constraints • Partner with client product owners to translate domain knowledge into technical designs • Mentor engineers on Azure architecture, event sourcing, durable orchestration, and HITL design patterns • Run agile delivery in 2-week sprints with monthly stakeholder demos, hypercare planning, and post-go-live support

Role Description As a Senior Data Engineer, you will design, build, and tune the data layer that powers our clients' mission-critical applications on Azure and SQL Server. You will own complex query performance, indexing strategy, and concurrency design, and you will architect the data access patterns that connect application code to the database through linq2db, LINQ-to-SQL, Entity Framework, and ADO.NET. You will partner with application engineers, architects, and product teams to deliver high-throughput, low-latency data solutions, and you will mentor others on database design, query optimization, and modern data engineering practices. Qualifications - A database craftsperson who treats query performance, indexing, and concurrency as first-class engineering concerns rather than afterthoughts. - A clear communicator who can explain execution plans, locking behavior, and data access trade-offs to engineers, architects, and product stakeholders. - Comfortable operating with ambiguity, capable of profiling production workloads and proposing concrete solutions backed by evidence. - A mentor who raises the bar for the team through code review, query review, and pattern guidance. - Customer-obsessed and outcome-focused, balancing delivery speed with the long-term health and scalability of the data platform. Requirements - Bachelor's Degree in Computer Science or a related discipline, or equivalent experience; MUST be proficient in written and spoken English (85%). - 5 to 8 years of professional data engineering or back-end engineering experience with a strong database focus. - Expert-level proficiency in SQL on SQL Server 2019+, including complex queries, window functions, set-based operations, query plan analysis, indexing strategy, statistics, RCSI, isolation levels, and Change Data Capture. - Expert-level proficiency in database performance tuning, including bottleneck identification, index design, query rewrites, and concurrency design under production load. - Strong proficiency in C# data access using linq2db, LINQ-to-SQL (DBML), Entity Framework, and ADO.NET; ability to choose the appropriate tool for each scenario and avoid ORM performance pitfalls. - Strong proficiency in Python for data engineering tasks, scripting, and automation. - Hands-on experience with Azure data services (Azure SQL, storage, networking, security) and deploying production data workloads in Azure. - Experience with database CI/CD, schema versioning, and migration tooling. - Solid Git, code review discipline, and familiarity with modern engineering practices including testing and observability. - Experience with Azure Data Factory, Synapse, or other Azure analytics services is a plus. - Experience designing event-driven or streaming data architectures is a plus. - Excellent analytical and problem-solving skills; strong communication, collaboration, customer orientation, innovation mindset, and adaptability under ambiguity. Responsibilities - Design and maintain SQL Server 2019+ schemas, indexes, and query patterns that meet performance, scalability, and concurrency requirements. - Analyze execution plans, identify bottlenecks, and tune queries, indexes, and statistics; advise on RCSI and isolation level choices. - Design and operate Change Data Capture (CDC) pipelines and other change-tracking patterns to support downstream consumers. - Implement and review data access using linq2db, LINQ-to-SQL (DBML), Entity Framework, and ADO.NET; choose the right tool for each scenario. - Translate business and application requirements into efficient SQL and C# data access code that is performant, testable, and maintainable. - Partner with application engineers to align ORM usage with database performance characteristics and avoid common anti-patterns. - Design and operate data solutions on Azure, including Azure SQL, storage, networking, and security configurations. - Contribute to CI/CD for database changes through migration scripts, schema versioning, and automated deployments. - Mentor engineers on database design, query optimization, and data access patterns; set standards for the team.

• Build reusable AI skills consumed across engagements: Document Intelligence, document summarization, data normalization, anomaly detection, matching engines, and compliance test runners • Design and train custom Document Intelligence neural models for client-specific document types • Implement RAG over enterprise document libraries using Azure AI Search with hybrid vector + keyword retrieval and semantic ranking • Build LLM reasoning chains using Azure OpenAI (GPT-4o for complex reasoning, GPT-4o-mini for high-volume classification) with prompt versioning and guardrails • Design agent orchestration in Azure AI Foundry for multi-step workflows: extract, search, reason, and generate output with tool-use grounding • Build evaluation harnesses, accuracy thresholds, and drift detection; tie outputs to confidence-gated HITL review tiers • Implement audit trail patterns for AI-assisted workloads: prompt/response logging, evidence chains, and SOC 2 aligned event sourcing • Mentor engineers on prompt engineering, RAG design, agentic patterns, and evaluation; contribute to Aubrant's AI engineering standards

Role Description As a Senior Data Engineer, you will design, build, and tune the data layer that powers our clients' mission-critical applications on Azure and SQL Server. You will own complex query performance, indexing strategy, and concurrency design, and you will architect the data access patterns that connect application code to the database through linq2db, LINQ-to-SQL, Entity Framework, and ADO.NET. You will partner with application engineers, architects, and product teams to deliver high-throughput, low-latency data solutions, and you will mentor others on database design, query optimization, and modern data engineering practices. Qualifications - A database craftsperson who treats query performance, indexing, and concurrency as first-class engineering concerns rather than afterthoughts. - A clear communicator who can explain execution plans, locking behavior, and data access trade-offs to engineers, architects, and product stakeholders. - Comfortable operating with ambiguity, capable of profiling production workloads and proposing concrete solutions backed by evidence. - A mentor who raises the bar for the team through code review, query review, and pattern guidance. - Customer-obsessed and outcome-focused, balancing delivery speed with the long-term health and scalability of the data platform. Requirements - Bachelor's Degree in Computer Science or a related discipline, or equivalent experience; MUST be proficient in written and spoken English (85%). - 5 to 8 years of professional data engineering or back-end engineering experience with a strong database focus. - Expert-level proficiency in SQL on SQL Server 2019+, including complex queries, window functions, set-based operations, query plan analysis, indexing strategy, statistics, RCSI, isolation levels, and Change Data Capture. - Expert-level proficiency in database performance tuning, including bottleneck identification, index design, query rewrites, and concurrency design under production load. - Strong proficiency in C# data access using linq2db, LINQ-to-SQL (DBML), Entity Framework, and ADO.NET; ability to choose the appropriate tool for each scenario and avoid ORM performance pitfalls. - Strong proficiency in Python for data engineering tasks, scripting, and automation. - Hands-on experience with Azure data services (Azure SQL, storage, networking, security) and deploying production data workloads in Azure. - Experience with database CI/CD, schema versioning, and migration tooling. - Solid Git, code review discipline, and familiarity with modern engineering practices including testing and observability. - Experience with Azure Data Factory, Synapse, or other Azure analytics services is a plus. - Experience designing event-driven or streaming data architectures is a plus. - Excellent analytical and problem-solving skills; strong communication, collaboration, customer orientation, innovation mindset, and adaptability under ambiguity. Company Description

• Define and drive the technical vision, engineering standards, and capability roadmap for the Data and AI Engineering Studio, ensuring alignment with Aubrant's Advisory, Studios, and Workbench ecosystem. • Recruit, mentor, and develop Studio Principals and Members through structured assessments, code reviews, knowledge sharing, and hands-on coaching on real engagements. • Drive innovation by evaluating and adopting emerging data and AI technologies, frameworks, and patterns; contribute reusable accelerators and reference architectures to Aubrant Workbench. • Architect, build, and deploy production-grade data platforms, analytics pipelines, machine learning models, and AI-powered solutions for enterprise clients, primarily on Azure. • Lead complex data and AI engagements end-to-end: discovery, architecture design, hands-on implementation, testing, and production cutover, ensuring solutions meet performance, governance, and security requirements. • Serve as the technical authority on client engagements, making real-time architectural decisions, resolving escalations, and ensuring delivery quality at the highest billing tier. • Partner with Advisory and Business Development to lead technical discovery sessions, shape proposals, define solution architectures, and develop effort estimates for data and AI opportunities. • Present Aubrant's data and AI capabilities to prospective clients, demonstrating technical depth and business acumen in executive-level conversations that build confidence and close deals. • Develop and maintain reusable pre-sales assets including reference architectures, demo environments, and proof-of-concept frameworks that accelerate the sales cycle. • Contribute data and AI accelerators to Aubrant Workbench, including reusable data pipeline templates, ML model serving patterns, AI agent frameworks, and governance modules. • Stay current with the rapidly evolving data and AI landscape: evaluate new services, assess their enterprise readiness, and integrate viable capabilities into Aubrant's delivery model. • Collaborate with the Woxsen University AI Research Partnership on applied research initiatives, translating academic breakthroughs into practical client solutions.

• Serve as the definitive platform authority for a complex, multi-module ServiceNow environment. • Own the technical direction of the platform, advise stakeholders on best practices, and translate business needs into scalable, high-quality solutions. • Operate within agile delivery cycles; contributing to sprint planning, backlog refinement, and iterative delivery with consistent output quality. • Partner with cross-functional teams across time zones, maintaining clear communication and shared accountability for outcomes. • Produce and maintain thorough technical documentation; design decisions, configuration specs, and runbooks; as a non-negotiable delivery standard. • Lead impact analysis prior to all changes and enforce change management discipline across environments. • Support platform upgrades, patch cycles, and health assessments with a proactive, structured approach. • Continuously drive improvements in platform performance, maintainability, and end-user experience.

• Lead and execute the migration of on-premises services to Microsoft Azure, ensuring minimal disruption and optimal performance. • Design scalable, secure, and highly available Azure-based solutions to meet project and business requirements. • Implement Infrastructure as Code (IaC) using Terraform to automate cloud infrastructure provisioning and management and CI/CD pipelines. • Implement and maintain security measures, access controls, and compliance standards to safeguard Azure resources. • Continuously monitor, optimize, and troubleshoot Azure infrastructure to ensure high performance and availability. • Optimize cloud spending by monitoring resource usage and recommending cost-effective solutions. • Develop and maintain automation scripts and processes to streamline cloud operations and CI/CD pipelines. • Create and maintain comprehensive documentation of Azure architectures, Terraform modules, CI/CD processes, and procedures. • Collaborate with cross-functional teams, including DevOps, developers, and project stakeholders, to ensure successful cloud migration and CI/CD implementation.