Role SummaryAs a
Senior Staff Software Engineer specializing in agentic applications, you will be the preeminent technical authority for our GenAI platform, setting architecture and strategy that spans multiple engineering organizations and shapes the company's long-term technology roadmap. You will lead the enterprise-wide integration of LLMs across our internal and customer-facing application portfolio. Your focus will be on driving cognitive automation at scale, transforming how the organization approaches decision-making and workflow automation, and establishing the engineering standards that define resilient, scalable, and observable distributed systems company-wide. You will operate as a force multiplier - influencing technical direction well beyond your immediate team and acting as a key partner to senior leadership in shaping the future of the platform.
Responsibilities- Architect and Own Agentic Systems at Enterprise Scale: Architect and lead the development of highly sophisticated, mission-critical intelligent agent systems that utilize LLMs to automate workflows, optimize operations, and elevate user experiences - setting technical direction across the entire engineering organization and influencing strategy at the company level.
- Define and Own Enterprise LLM Integration Strategy: Own and drive the multi-year technical vision for integrating LLMs across the company's software ecosystem, ensuring robust, scalable, and maintainable communication and data exchange. Serve as the ultimate technical authority and final escalation point for LLM architecture decisions across the organization.
- Lead the Enterprise Cognitive Automation Roadmap: Partner directly with senior leadership, product executives, and engineering leaders to define and own the company-wide strategic direction for cognitive automation. Leverage LLMs to transform complex cognitive tasks - such as information extraction, summarization, and question answering - into scalable, repeatable capabilities across the enterprise.
- Champion Scalable System Design at Organizational Scale: Take ultimate technical ownership of the entire development lifecycle for the organization's most strategically important machine learning-powered tools and applications. Establish technical frameworks and architectural patterns that are adopted company-wide and that outlast individual projects or teams.
- Define and Uphold Engineering Standards Across the Company: Set the engineering culture at the organizational level. Establish and enforce industry-leading standards for building production-grade, distributed machine learning solutions, and ensure consistent adoption across all engineering teams, not just your own.
- Drive Technical Consensus and Shape Company Direction: Continuously research and experiment with emerging trends in machine learning, AI agents, and distributed systems. Translate findings into actionable technical strategy with measurable, company-wide impact, and represent the organization's technical point of view in industry and cross-company forums where relevant.
- Lead Cross-Functional and Executive Alignment: Work closely with machine learning engineers, product teams, and senior/executive leadership to gather requirements, define strategic scope, and deliver high-impact solutions. Own technical alignment across the entire organization and serve as the primary engineering representative at the executive level.
- Grow and Elevate Engineering Talent Organization-Wide: Mentor and elevate engineers at all levels, from mid-level to principal/staff, fostering a culture of technical excellence, innovation, and continuous learning across the company. Own hiring strategy and serve as the final technical bar-raiser for senior and staff-level hires.
Qualifications- Advanced Degree: Bachelor's, Master's, or Ph.D. in Computer Science, Machine Learning, or a related field.
- Proven Experience: 15+ years of hands-on experience in software engineering, with deep expertise in designing and building large-scale distributed systems. Extensive, hands-on experience architecting and deploying complex agentic applications leveraging LLMs in production at enterprise scale. Demonstrated track record of company-wide, and ideally industry-recognized, technical impact.
- Strong Technical Skills: Expertise in Golang is strongly preferred. Deep proficiency in Python or similar languages, along with expert-level knowledge of cloud and container frameworks such as AWS and Kubernetes. A proven track record of architecting highly scalable, fault-tolerant, and observable distributed systems used across an entire organization.
- Deep Understanding: Expert-level, authoritative grasp of machine learning principles, algorithms, and evaluation metrics, as well as software engineering best practices for distributed systems at scale.
- Production Experience: Demonstrated success owning the design, deployment, and operation of mission-critical backend software in high-stakes production environments at company-wide organizational scale.
- Collaborative Spirit and Technical Leadership: Exceptional communication and influencing skills, with a proven ability to build consensus among executive stakeholders, define engineering culture at the organizational level, and align the entire company on complex, high-stakes technical decisions.
- Passion for Innovation: A genuine and demonstrated passion for advancing the state of the art in machine learning and natural language processing, with a track record of translating cutting-edge research into durable business impact at scale.
Total RewardsFull-time positions include base salary, eligibility for an annual performance bonus, and eligibility for equity.
In addition to base salary, Rivian and Volkswagen Group Technologies offers benefits tailored to the local market. For more information on the benefits available for full-time employees, check out our Global Benefits Site.
External candidates can apply for this role through the Rivian and Volkswagen Group Technologies careers site (https://rivianvw.tech/#careers). If you are a current employee, please apply through our internal job board
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