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Mountain View, California, United States
Onsite
Location: Mountain View, CA — On-site
Granica is building the efficiency and intelligence layer for enterprise AI.
Enterprises already operate enormous proprietary data estates and increasingly build AI systems on top of them, but the underlying infrastructure remains fragmented, expensive, and inefficient.
Granica is building across three related layers:
Crunch — efficiency for enterprise data
Large Tabular Models — intelligence for enterprise structured data
Myelin — efficiency for stateful, long-running AI agents
Crunch continuously optimizes large enterprise lakehouse environments across technologies such as Apache Spark, Iceberg, Delta Lake, Parquet, Snowflake, and Databricks — reducing storage and compute cost while improving data layout and operational efficiency.
Granica has already processed hundreds of petabytes of customer data for companies including Snap, Pinterest, Lyft, and ShareChat, with customers able to validate meaningful savings within weeks.
Granica is hiring a Forward Deployed Engineer to become the technical bridge between our customers, Engineering, Product, and GTM teams.
You will work directly inside complex enterprise data environments to understand workloads, investigate performance and cost problems, deploy Granica, run technical evaluations, and turn the results into clear customer recommendations.
This is a highly hands-on role. You should be comfortable moving from a customer conversation to Spark debugging, SQL analysis, performance benchmarking, architecture decisions, and an executive-facing explanation of the technical and economic tradeoffs.
As one of Granica’s first dedicated Forward Deployed Engineers, you will also help define how the function operates as we scale.
Lead technical discovery with enterprise data, infrastructure, and AI teams
Understand customer data architecture, workloads, constraints, and business priorities
Deploy and configure Granica in complex customer-controlled environments
Investigate performance, reliability, storage, and compute-cost problems across large data platforms
Debug and optimize Apache Spark workloads and related distributed-data systems
Analyze table layouts, file structure, partitioning, compaction, and data-maintenance behavior
Design and execute technical evaluations and proofs of value with clear success criteria
Establish trustworthy measurements and translate results into defensible customer recommendations
Explain technical tradeoffs across performance, cost, reliability, and operational complexity
Partner with Account Executives during technical discovery, evaluations, and enterprise sales cycles
Present findings and business value to engineers, architects, and executive stakeholders
Translate recurring customer problems into Product and Engineering priorities
Build repeatable deployment, troubleshooting, benchmarking, and evaluation playbooks
5+ years in Forward Deployed Engineering, Data Engineering, Solutions Architecture, Sales Engineering, or a similarly hands-on technical role
Strong hands-on Apache Spark experience, including production workloads, debugging, performance tuning, and distributed execution behavior
Strong understanding of distributed data systems and modern cloud data infrastructure
Experience with lakehouse technologies such as Apache Iceberg, Delta Lake, Parquet, Hive, or comparable systems
Strong SQL skills and proficiency in Python, Scala, Java, or another relevant programming language
Experience diagnosing performance or reliability problems using data and experimentation
Ability to reason about infrastructure economics, including storage, compute, and performance tradeoffs
Strong customer communication skills and the ability to explain technical recommendations clearly
High ownership and comfort operating without an established playbook
Ability to work from our Mountain View office five days per week and travel to customer locations when needed
Work directly on some of the largest enterprise data environments in production
Solve technically difficult problems where improvements can translate directly into substantial customer savings
Work across Spark, lakehouse systems, distributed infrastructure, AI, and emerging enterprise data architectures
Partner directly with customers, company leadership, Product, Engineering, and GTM
Help build Granica’s Forward Deployed Engineering function from the ground up
Influence both product direction and how Granica engages technically with customers
Join a small team working at the intersection of enterprise data infrastructure and AI
Competitive salary, meaningful equity, and performance bonus for top performers
401(k) with company match, comprehensive health coverage, and unlimited PTO
Daily catered meals in our Mountain View office
Support for research, publication, and conference participation
At Granica, you'll help build the next generation of enterprise AI—from exabyte-scale data infrastructure, Large Tabular Models (LTMs), and stateful AI agents. Together, we're creating the infrastructure that enables enterprises to own their data, own the intelligence built on it, and scale both efficiently.
