Forward Deployed Engineer

Department: GTM

Location: Bay Area Office

Compensation: $160K – $220K • Offers Equity

Employment Type: FullTime

Forward Deployed Engineer / Sales Engineer

Location: Mountain View, CA — On-site

About Granica

Granica builds AI infrastructure for enterprises operating massive data environments.

Our platform helps data and engineering teams reduce storage and compute costs, improve performance and reliability, and prepare large datasets for analytics and AI.

Granica’s products include:

• Crunch — continuous optimization for enterprise lakehouse data

• Myelin — stateful infrastructure for long-running AI agents

• Large Tabular Models — foundation models designed for enterprise tables

Together, we are building the infrastructure that enables enterprises to own their data, own the intelligence built on it, and scale both efficiently.

Granica has demonstrated approximately $200K in annualized value per petabyte and verified customer value within weeks.

About the Role

Granica is hiring a Forward Deployed Engineer / Sales Engineer to lead technical engagements with enterprise customers from initial discovery through evaluation and deployment.

You will work directly with data platform teams, engineers, architects, and technical executives to understand their environments, identify high-value use cases, design proofs of value, and demonstrate measurable technical and economic impact.

This is a hands-on role for someone who can operate across customer engineering, technical sales, product, and engineering.

What You’ll Do

• Lead technical discovery with enterprise data, infrastructure, and AI teams

• Understand customer architecture, workloads, constraints, and business priorities

• Design and execute proofs of value with clear success criteria

• Deploy and configure Granica in complex customer environments

• Analyze data-platform performance, reliability, and infrastructure costs

• Troubleshoot issues across data, compute, permissions, networking, and integrations

• Partner with Account Executives throughout complex enterprise sales cycles

• Present technical findings and business value to engineering and executive stakeholders

• Translate customer feedback into product and engineering priorities

• Build repeatable technical playbooks and evaluation frameworks

What We’re Looking For

• 5+ years in Forward Deployed Engineering, Sales Engineering, Solutions Architecture, Data Engineering, or a similar technical customer-facing role

• Deep hands-on expertise with Apache Spark, including debugging, performance tuning, cluster behavior, and production workloads

• Strong knowledge of modern data platforms, distributed systems, and cloud infrastructure

• Experience with lakehouse technologies such as Iceberg, Delta Lake, or comparable systems

• Proficiency in SQL and at least one programming language

• Experience leading enterprise technical evaluations, proofs of concept, or deployments

• Strong troubleshooting and customer communication skills

• High ownership and comfort operating in a fast-moving startup

• Ability to travel to customer locations when required

Why Join Granica

• Work on foundational infrastructure for enterprise data and AI

• Partner directly with customers, company leadership, Product, and Engineering

• Help define Granica’s technical GTM motion and Forward Deployed Engineering function

• Join an early-stage team solving high-value infrastructure problems at massive scale

• Have direct influence on product direction, customer outcomes, and company growth

Compensation & Benefits

• 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.