Partner Solutions Architect

About the role

This position involves working with LanceDB's strategic partners, including system integrators, cloud providers, and technology alliances. You will serve as a technical expert, helping partners implement and scale LanceDB solutions for their enterprise clients. This role requires a combination of deep technical knowledge in distributed systems and AI/ML, along with strong relationship-building capabilities.

Key facts

What you'll do

• Lead technical onboarding, training, and certification programs for partner engineers and architects.
• Collaborate with alliance and field teams on proofs-of-concept, design reviews, and architectural validations for complex cloud environments.
• Create and maintain technical content for partners, including reference architectures, integration guides, deployment blueprints, and sample code.
• Act as a technical bridge between partners and LanceDB's product and engineering teams, influencing the product roadmap with partner feedback.
• Participate in joint business planning and support technical marketing events and campaigns.
• Share best practices through technical blogs, whitepapers, open-source contributions, and presentations at industry conferences.

Requirements

• Over 10 years of experience in customer or partner-facing technical roles, such as Solutions Architecture, Partner Engineering, Sales Engineering, or ML Infrastructure, with a focus on data platforms or distributed systems.
• Demonstrated experience working with or within a partner ecosystem, understanding how partners bring solutions to market.
• Strong understanding of distributed systems concepts like sharding, replication, partitioning, performance tuning, and container orchestration (Kubernetes, cloud object storage).
• Proficient in Python and willing to work with Rust for writing and debugging production-grade integration code or SDK extensions.
• Excellent presentation and communication skills, capable of explaining complex data infrastructure to various audiences.
• Ability to work independently and adapt to fast-paced, evolving environments.

Nice to have

• Practical experience building or supporting vector search pipelines, RAG applications, feature stores, or multimodal AI architectures.
• Experience with open-source data frameworks and infrastructure orchestration tools like Apache Spark, Ray, Delta Lake, Terraform, Kafka, or Airflow.
• Familiarity with modern observability and monitoring stacks such as Prometheus, Grafana, or OpenTelemetry for troubleshooting distributed workloads.
• Active involvement in open-source communities or a portfolio of developer-focused technical content.

Skills & tools

• Python
• Rust
• Kubernetes
• Cloud object storage
• Distributed systems concepts
• Vector search pipelines (bonus)
• RAG applications (bonus)
• Apache Spark (bonus)
• Ray (bonus)
• Delta Lake (bonus)
• Terraform (bonus)
• Kafka (bonus)
• Airflow (bonus)
• Prometheus (bonus)
• Grafana (bonus)
• OpenTelemetry (bonus)

Practical notes

This is a remote, full-time position. You will join a team focused on open-source AI infrastructure. The role involves defining how the AI ecosystem integrates with and scales LanceDB.