This role involves deploying, optimizing, and extending Spice.ai solutions in production environments, collaborating on product improvements, and working directly with customers to drive AI adoption.
Building data-driven AI applications and agents is too complex, even for advanced developers. At Spice AI, we’re making it simpler by helping developers combine code, data, and AI to build truly intelligent, decision-making systems. Our mission is to make this as easy as creating a modern web page.
We created Spice.ai OSS, a portable AI database written in Rust with a unified SQL interface to query, materialize, and accelerate data from any source, co-located with machine learning models. By bringing compute, data, and models together, Spice OSS enables secure AI-Feedback-Loops (AI-Fly-Wheels) for apps and agents to learn and adapt. We just announced the 1.0-stable release of Spice.ai OSS.
For a deeper dive into the vision, watch Luke's CMU Databases talk on Spice.ai OSS at https://www.youtube.com/watch?v=tyM-ec1lKfU and read his Materialized View interview at https://materializedview.io/p/building-a-cdn-for-databases-spice-ai.
We're also building the Spice.ai Cloud Platform, offering managed, cloud-scale Spice.ai OSS along with tools for high-performance SQL, machine learning training, and inference in an interconnected AI backend-as-a-service.
At Spice AI, we hire for MEI: Merit, Excellence, and Intelligence. We're looking for exceptional, top-tier engineers - A players - who are driven to solve hard problems and push the boundaries of what's possible for AI.
This role requires a Forward Deployed Engineer to embed with customers and partners, accelerating adoption through direct engineering contributions. Responsibilities include deploying, optimizing, and extending Spice.ai solutions in production environments, while collaborating on product improvements.
If open source, distributed systems, and real-world search & AI deployment drive you, apply.
Who We Are Looking For
- An exceptional engineer.
- A problem solver who starts with customer problems and solves them with technology.
- A thinker who challenges the status quo, rejects the current world model, and builds better for everyone.
- A positive force who asks what's possible instead of focusing on limitations.
- Someone who views work as meaningful, not just a job.
- Comfortable with ambiguity and unknowns, leading by creating clarity.
- Passionate about high performance with high standards.
What We're Looking For
- 5+ years in engineering roles, with focus on deploying data, search, and AI systems in enterprise environments.
- Experience designing, implementing, and scaling production database engines, distributed systems, search engines, and data & AI pipelines.
- Track record of strong design, architectural, engineering, and product decisions in customer-facing contexts.
- Excellent communication skills.
- Ability to ramp up quickly and deliver impact.
- Contributions to open-source projects preferred.
- Experience with Apache infrastructure, CNCF stack, or cloud-native development.
- Deep knowledge of databases, data warehousing, data lakes, search, virtualization, and mesh principles.
- Proficiency with Databricks, Snowflake, Starburst, Dremio, ElasticSearch, or similar.
- Strong SQL skills in queries, syntax, modeling, and optimizations.
- Familiarity with data storage like HDFS, Amazon S3, and relational databases.
- Skills in data integration, including ETL/ELT, ingestion, and transformation.
- Ability to tune performance and optimize systems.
- Knowledge of data security, privacy, authentication, authorization, and encryption.
- Problem-solving for complex data challenges.
- Presentation skills for technical and executive audiences.
- Ability to explain concepts to technical and non-technical stakeholders.
- Relationship-building with customers and partners.
- Willingness to travel 20%+ based on customer needs.
In This Role, You'll
- Embed with enterprise customers and partners to deploy Spice.ai OSS/Enterprise and Cloud Platform in production.
- Build, configure, and optimize proof-of-concepts and deployments for performance, scalability, and security.
- Collaborate with engineering to incorporate customer feedback into core product features.
- Resolve technical blockers, debug issues, and extend Spice.ai capabilities on-site or remotely.
- Design end-to-end architectures using Spice.ai for data querying, search, and AI inference.
- Identify expansion opportunities and drive adoption of new features.
- Work side-by-side with founders as a leader in customer success engineering.
- Contribute to Spice.ai OSS improvements based on real-world usage.
- Own initiatives to refine offerings and deliver superior developer experiences.
Your First 90 Days
- First week: Deploy a Spice.ai instance for a customer scenario and fix a deployment issue.
- First month: Ramp up, lead a POC deployment, and contribute optimizations to Spice.ai OSS.
- 30-60 days: Take ownership of a customer deployment area, from architecture to production rollout.
- 60-90 days: Propose and execute a technical strategy for scaling customer integrations.
About Spice AI
Founded in June 2021 by Microsoft and GitHub alumni Luke Kim and Phillip LeBlanc, Spice AI creates technology to help developers build intelligent applications and agents that learn and adapt.
Before co-founding Spice AI, Luke was the co-creator of Azure Incubations in the Office of the Azure CTO, where he led cross-functional engineering teams to create and develop technologies including Dapr and OAM.
Spice AI is backed by some of the top industry angel investors and leaders, including Nat Friedman, Mark Russinovich, CTO of Microsoft Azure, and Thomas Dohmke, CEO of GitHub, who is also on the board.
Spice AI also has notable VC backing from Madrona Venture Group, Basis Set Ventures, Founders' Co-op, and Picus Capital.
Learn more:
- On TechCrunch and GeekWire
- About the team at spice.ai/careers
- The Spice.ai general availability announcement blog post
- The Spice.ai OSS project announcement blog post
Top Skills
Amazon S3
Databricks
Dremio
Elasticsearch
Hdfs
Rust
Snowflake
SQL
Starburst
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