• Design and develop AI-enabled services and applications using Python and modern cloud-native architectures. • Integrate large language models (LLMs) and AI APIs into production systems to enable intelligent automation and decision support. • Build scalable microservices and APIs that support AI-driven workflows and data processing. • Develop pipelines and services that process structured and unstructured data to support intelligent applications. • Implement secure APIs and event-driven architectures that support data integration and AI-enabled services. • Optimize AI-powered applications for performance, reliability, and scalability in cloud environments. • Collaborate with engineers, product teams, and stakeholders to translate AI concepts into deployable solutions. • Take on additional tasks and responsibilities as needed to support team objectives and ensure the success of the project.

• Architect and optimize observability environments through software engineering best practices. • Build automation scripts and tools to streamline observability instrumentation and deployment. • Integrate observability into CI/CD pipelines using infrastructure-as-code (IaC) and configuration management tools. • Conduct observability code reviews and implement automated validation checks. • Build AI-native tools for autonomous issue detection and resolution. • Lead the design of distributed systems focused on reliability, scalability, and performance. • Manage data routing, transformation, and endpoint monitoring integrations. • Mentor junior engineers and foster a culture of continuous improvement. • Collaborate across teams to align observability strategies with business goals. • Communicate technical insights and recommendations to leadership.

• We are hiring a Full Stack Engineer to join a modern and exciting program in the VA space. • Working hand in hand with other engineers in developing end-to-end testing solutions and API endpoints and services. • Day to day work will involve writing code, developing tests, and debugging.

• Build and maintain tools that dramatically increase SDR and AE productivity across the full sales cycle • Design automated lead enrichment pipelines that append firmographic, technographic, and intent data to inbound and outbound leads in real time • Build prospecting automation workflows that surface high-fit accounts based on ICP criteria and buying signals • Architect CRM workflow automations in HubSpot to enforce pipeline hygiene, automate stage progression, and trigger internal notifications • Develop AI-driven outbound messaging sequences that personalize at scale using prospect-specific context • Create meeting booking automation to reduce scheduling friction and increase connect rates • Create the systems that generate and nurture a pipeline without constant manual intervention • Build automated outbound campaign engines that execute multi-channel sequences (email, LinkedIn, phone) on a defined cadence • Develop AI-generated personalized outreach at scale, adapting messaging to prospective industry, role, and stage • Implement data scraping and lead sourcing workflows to build targeted prospect lists from public data sources • Create trigger-based prospecting systems (e.g., a marina raises funding or announces expansion → AI detects → personalized outreach generated → SDR notified) • Support product-led growth workflows that convert trial users into qualified pipeline • Build and manage AI SDR assistants that handle initial prospect engagement, qualification, and handoff • Develop AI-generated demo environments and personalized demo prep packets • Create AI proposal and SOW generation tools that reduce deal cycle time • Implement AI call summary and coaching workflows that feed insights back into the sales process • Build AI-based prospective research tools that deliver actionable account briefs before every call • Build the dashboards and models that give leadership real-time visibility into revenue performance • Design pipeline analytics dashboards that track stage velocity, conversion rates, and bottlenecks • Build and refine lead scoring models that prioritize the highest-value opportunities for sales • Implement end-to-end conversion tracking across marketing and sales touchpoints • Create experimentation analysis frameworks to measure the impact of GTM tests • Develop attribution systems that connect marketing spending to closed revenue • Run a high-velocity experimentation program that continuously improves GTM performance • Test different ICP segments to identify under-penetrated verticals within the marina and entertainment industry • A/B test outreach messaging across channels, personas, and value propositions • Run pricing and packaging experiments in collaboration with product and finance • Optimize the demo → POC → close conversion funnel with structured tests and measurement • Document findings in a shared experiment log to build institutional knowledge