Principal Software Engineer
| Company | DataRobot |
|---|---|
| Location | Boston, MA, USA, Toronto, ON, Canada, Berlin, Germany, Munich, Germany |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | |
| Experience Level | Senior, Expert or higher |
Requirements
- 8+ years of software engineering experience
- 3+ years in AI/ML systems (Generative AI preferred)
- Deep expertise in scalable systems: Distributed computing, containerization (Docker/K8s), and multi-cloud deployments (AWS/GCP/Azure/Openshift)
- Deep expertise in software craftsmanship: Python, API design, and infrastructure-as-code (Terraform, Pulumi)
- Proven track record of delivering multi-year, high-impact projects with cross-functional dependencies
- A systems thinker who balances innovation with operational pragmatism (e.g., cost-to-serve, technical debt)
- Exceptional communication and influence skills
Responsibilities
- Shape the long-term technical strategy for Generative AI at DataRobot, ensuring our systems are scalable, maintainable, and aligned with business goals
- Lead architectural decisions for GenAI tooling and GenAI systems
- Anticipate technical risks and propose mitigation strategies before they become roadblocks
- Build, ship and operate critical AI infrastructure, balancing rapid iteration with long-term technical health
- Solve cross-pillar challenges, such as optimizing LLM latency/cost, improving Agentic workflows, or ensuring reproducibility in generative outputs
- Drive operational excellence by improving observability, reliability, and performance of AI systems in production
- Act as the technical advisor to engineering leadership and product teams, influencing roadmap priorities
- Mentor Staff/Senior Engineers, elevating the team’s technical bar through design reviews, best practices, and knowledge sharing
- Foster a culture of innovation and rigor, ensuring AI solutions are both cutting-edge and production-ready
- Partner with Research, Product, and GTM teams to align technical efforts with customer needs and market opportunities
- Communicate complex technical concepts to executives and non-technical stakeholders, enabling data-driven decisions
Preferred Qualifications
- Deep expertise in Generative AI stack: LLMs (open/closed-source), fine-tuning, RAG, orchestration, and evaluation metrics
- Experience with MLOps tools and AI-specific infra (e.g., vector DBs, GPU optimization)
- Contributions to open-source AI projects or published research in ML/GenAI
- Background in enterprise SaaS or B2B AI products