Top Tech Jobs & Startup Jobs

Build and support AI agents, automated workflows, system integrations, and generative AI solutions using Azure AI, Copilot Studio, Power Automate, Tines, and supporting code. Collaborate with stakeholders to define requirements, test and deploy reliable automations, implement logging and security, troubleshoot production issues, document solutions, and measure business outcomes. Integrate platforms such as Teams and Salesforce through APIs, webhooks, and connectors while validating AI-generated outputs.

Build and operate reliable batch and streaming data pipelines, curated analytical data models, and data quality controls. Own production monitoring, incident response, performance and cost optimization, security, governance, lineage, and documentation. Partner with analysts, data scientists, product engineers, and customers to define durable data contracts and deliver Azure-based data platforms. Apply Python, PySpark, SQL, CI/CD, infrastructure as code, and modern lakehouse technologies.

Lead the strategy, architecture, and implementation of enterprise Azure data and AI solutions. Design scalable architectures using Microsoft Fabric, Synapse, Databricks, Azure databases, and AI services. Provide technical leadership, mentor engineering teams, oversee integrations, establish standards, and ensure security, governance, and operational excellence. Engage clients as a trusted technical advisor through workshops and executive presentations while partnering with project managers to deliver complex initiatives.

Provides L3/L4 operational support and engineering for Citrix and Azure Virtual Desktop environments. Responsibilities include troubleshooting, platform administration, endpoint and identity management, patching, monitoring, disaster recovery, automation with Infrastructure as Code, performance and cost optimization, client advisory, documentation, incident response, and mentoring. The role supports multiple enterprise customer environments while improving reliability, security, governance, and service delivery.

Provides L3 operational support, troubleshooting, optimization, automation, security, and modernization for customer Azure environments. Manages Azure infrastructure, networking, identity, monitoring, governance, disaster recovery, and infrastructure as code. Serves as a client technical advisor, supports incident response and managed services onboarding, develops runbooks, and drives FinOps cost optimization and reliability improvements across multiple production environments.

Generates net-new business opportunities through outbound prospecting, cold calling, email, LinkedIn, and strategic outreach. The role researches target accounts, engages executive decision-makers, qualifies leads, schedules meetings, communicates technology solutions, and meets activity and pipeline targets. The representative partners with Sales, Marketing, and Consulting teams on AI, security, and cloud sales initiatives while developing expertise through mentorship and certifications.

Build and refine AI-powered automation solutions for business workflows. Partner with stakeholders to identify automation opportunities, apply generative AI and conversational agents, test solutions against real-world data, document architectures, communicate results, and support deployment. Interns gain hands-on experience with Microsoft AI and automation technologies while researching emerging tools and measuring operational impact.

Designs and sells complex managed services solutions while developing scalable service offerings, pricing models, documentation, standards, and enablement assets. Leads technical discovery, solution architecture, proposals, negotiations, deal governance, vendor alignment, and presales-to-delivery handoffs. Partners with Sales, Finance, Legal, Engineering, Operations, Delivery, clients, and technology providers to ensure profitable, contractually sound, and operationally ready services across cloud, infrastructure, security, end-user computing, data protection, service management, and AI-enabled technologies.

Build and operate Microsoft Fabric and Azure data and machine learning platforms for enterprise clients. Responsibilities include workspace governance, data pipelines, CI/CD, orchestration, data quality gates, identity and secrets management, versioning, monitoring, model operationalization, Power BI integration, and client handoff documentation. The role requires production data platform engineering experience, scheduled ML workload deployment, strong Python and SQL, Azure security expertise, and collaboration with distributed US-based delivery teams.

Lead end-to-end Azure infrastructure engagements: design, implement, validate, document, and transition environments to managed services. Use Cloud Adoption Framework and Well-Architected principles, perform migrations with Azure Migrate, ensure security, resiliency, operational readiness, automate via IaC, troubleshoot complex issues, and enable knowledge transfer for managed services.