• Administrar e desenvolver soluções na plataforma ServiceNow; • Contribuir para a evolução da plataforma, automação de processos, integrações sistêmicas e melhoria contínua dos serviços de TI; • Participar de iniciativas estratégicas relacionadas à governança, gestão de serviços, infraestrutura e transformação digital.

• Design and implement services and features within established architectural patterns. • Contribute to written technical designs and implementation plans, collaborating with senior engineers to ensure alignment on broader system impact. • Review approaches and trade-offs with the engineering team to maintain consistency, scalability, and reliability across the platform. • Build software with security, privacy, and compliance considerations in mind, partnering with internal teams as needed. • Develop, test, and deploy production-ready code, including building and maintaining automated tests, to balance delivery timelines with system stability, reliability, and maintainability. • Apply sound technical judgment when refactoring existing systems or implementing pragmatic fixes, documenting decisions and communicating trade-offs clearly. • Participate actively in code reviews and uphold established engineering standards and best practices. • Proactively identify technical risks, performance bottlenecks, and system weaknesses, proposing solutions and collaborating with senior engineers on higher-impact remediation efforts. • Participate in production support and incident response, contributing to investigation and resolution efforts. • Contribute to monitoring, logging, and alerting practices, and assist with incident investigation, root cause analysis, and follow-up improvements to support system health and reliability. • Create and maintain clear technical documentation, including implementation notes, architectural context, and code-level documentation. • Use written communication to keep work visible, reduce reliance on synchronous meetings, and support effective collaboration in a distributed environment. • Partner with Product and Operations teams to understand requirements and deliver reliable technical solutions. • Collaborate effectively with distributed team members across time zones using asynchronous tools such as Slack, Jira, and shared documentation. • Support continuous improvement initiatives that enhance system reliability, developer efficiency, and operational clarity.

• Design, develop, and deliver safe, scalable, and robust real-time software for mass production grade autonomous vehicle systems directly contributing to safer roads and economically viable AI deployment. • Conduct in-depth algorithm analysis, optimization, and iteration to enhance efficiency and accuracy across the AV stack. • Architect scalable continuous learning system for deploying new ML models, monitoring their performance, and prioritizing improvements. • Collaborate with platform, embedded, and AI teams to ensure cohesive development, validation, and integration of ML based perception, prediction, and planning. • Stay abreast of industry trends and emerging tools in high-performance computing, real-time systems, and AI-driven mobility.

• Build and maintain AI-powered pipeline generation infrastructure — property trigger monitoring from sources like ConstructConnect, ALN, and CoStar; account and building scoring models; and outreach automation that operationalizes signals into rep-ready pipeline • Develop and operate a library of role-specific AI agents and prompt templates (i.e. post-call summarization, outreach personalization, next-best-action guidance, and deal coaching), while owning the prompt engineering and agent reliability infrastructure that keeps them running at scale • Design and build internal tools for reps and operators, such as building and partner maps, call preparation and proposal drafting tools, deal coaching dashboards, and other lightweight applications that give the Sales team self-serve access to intelligence and workflow acceleration • Analyze Salesforce data, call transcripts, pipeline patterns, and conversion signals to identify where revenue constraints are sharpest and which automation investments will move the most important levers; use those findings to set the automation agenda, measure the impact of what ships, and feed a continuous improvement loop between what gets built and whether it’s working • Own the rep-facing intelligence layer — the natural language query interface that gives reps and operators self-serve access to pipeline data, and the conversational intelligence pipeline that extracts Gong signal into CRM fields and surfaces actionable insights from call activity • Govern GTM data integrity across the Sales stack ensuring that Salesforce reflects activity accurately, opportunity stages are enforced before forecast pollution occurs, and account and building ownership conflicts are caught and resolved in real time • Maintain the integration and data quality relationships that keep the automation layer stable, working with Business Systems on integration reliability and with the Revenue Intelligence Lead to ensure agent inputs are clean, governed, and properly routed when issues surface