Jobs at Applied Systems

Partner with Go-to-Market leaders to lead full-cycle recruiting for Sales and related GTM roles. Build sourcing strategies and pipelines, design structured interviews, use recruiting metrics to track progress, coach hiring teams, and collaborate with cross-functional partners to deliver inclusive hiring and successful onboarding.

The Sales Consultant will expand market presence among P&C carriers and MGAs by generating leads and closing sales, while engaging in consultative selling to address client needs.

Partner with sales to perform technical and operational discovery for P&C carrier prospects, deliver demos and proofs-of-concept using REST APIs, Postman, webhooks and Python scripting, document solutions and RFIs/RFPs, coordinate site visits, and enable seamless handoffs while supporting up to 50% travel.

As a Client Executive, you will manage customer accounts, drive adoption of Cytora's AI solutions, and build relationships with clients while aligning strategic goals through business reviews and workshops.

Lead North America agency adoption and engagement for Applied's commercial collaboration portfolio. Set strategy, build scalable operating models and playbooks, align cross-functional teams, and personally lead executive agency engagements and large migrations to drive day-to-day usage and bound premium. Combine human-led and digital adoption motions and reinforce network effects between agencies and carriers.

As a Business Development Associate, you'll manage inbound leads, connect clients with solutions, and develop relationships while advancing in your career.

Lead product analytics for a B2B SaaS product: define metrics and measurement frameworks, analyze user behavior and product performance, build self-service dashboards, partner cross-functionally to link usage to business outcomes, and translate data into strategic recommendations for product roadmap and GTM decisions.

Lead and build a product analytics function: define KPI framework, instrumentation, and self-serve analytics using Pendo and BI tools. Partner cross-functionally to measure product performance, surface insights, influence roadmap and embed AI-powered analytics into product lifecycle.

As a Software Development Engineer in Test, you'll create and conduct automated tests, resolve technical issues, and collaborate with development teams to ensure software quality.

Lead a new data engineering team to define standards, drive cross-functional AI-driven initiatives, and provide hands-on guidance in SQL optimization, data modeling, and the GCP data/streaming stack. Balance technical leadership with people management, coach engineers, promote AI-assisted workflows, and collaborate with Product and Architecture to build a standardized data ecosystem.

Build and deploy production micro-apps and LLM-powered agents on a governed GCP platform. Integrate AI with systems (Salesforce, Slack, NetSuite, SQL), harden apps with auth, secrets, CI/CD, logging and monitoring, automate maintenance, and implement evaluation and observability for model quality and drift.

Design, deploy, and operate enterprise network infrastructure across data centers and cloud (GCP, AWS, Azure). Manage VPCs, VPNs, BGP, F5 BIG-IP, hybrid connectivity, and observability. Build IaC and automation with Terraform, GitLab CI/CD, and Ansible. Maintain monitoring, documentation, and participate in on-call support for critical incidents.

Contribute to building and hardening micro-apps and AI integrations on a shared GCP platform. Complete bug fixes and small features, participate in code and design reviews, apply security and software development best practices, monitor applications and follow runbooks, and use AI tools to assist development, testing, and documentation while learning from senior engineers.

Lead intake, roadmap, and governance for an AI automation/platform team. Harden and ship business-built AI apps to production with secure GCP platforms, define acceptance criteria and responsible-AI gates, manage vendor buy-vs-build decisions, drive adoption, measure outcomes, and manage AI economics and stakeholder communication.

Build, model, and maintain scalable BigQuery-based data solutions on GCP. Implement performant data models, storage partitioning/clustering, ETL improvements, data validation, and documentation. Collaborate with architects, data scientists, and engineers to deliver governed, high-quality data for reporting and AI initiatives.

Lead strategy and roadmap for AI-powered SaaS features; collaborate with engineering, data science, UX, and GTM teams to define problems, run discovery and experiments, manage backlogs, deliver product outcomes, and drive post-launch adoption and performance improvements.

Lead strategy and delivery of AI-powered, agentic product features for a SaaS insurance platform. Define roadmaps, KPIs, ROI, and success criteria; collaborate with engineering and data science to prototype, test, and launch; drive adoption, mentor junior PMs, and align cross-functional teams from discovery through GTM.

Lead design and governance of enterprise-scale data architecture (warehouses, lakehouses, streaming). Define standards for data quality, lineage, observability, and AI-enabled workflows. Mentor engineers, serve as technical escalation, and translate business needs into long-term data architecture and governance strategies.

Lead portfolio strategy and operating layer for Product and Engineering: build prioritization frameworks, connect roadmaps to financial goals, define reporting/metrics for E-Team and Board, and drive cross-functional initiatives and decision-making.

Design, build, and operate enterprise-scale multi-cloud infrastructure (Azure primary, GCP, AWS exposure). Own landing zones, Terraform modules, production AKS/GKE Kubernetes, Vault secrets, hybrid networking, CI/CD pipelines, monitoring, DR, and automation (Ansible, Python/Bash). Mentor engineers, document runbooks, and collaborate with security, application teams, and leadership to ensure secure, reliable, cost-optimized cloud platforms.