Agilesoft
Overview
Candidates should take the time to read all the elements of this job advert carefully Please make your application promptly. Join to apply for the
Engineering Manager
role at
Agilesoft .
Granica is redefining how enterprises prepare and optimize data at the most fundamental layer of the AI stack—where raw information becomes usable intelligence. Our technology operates deep in the data infrastructure layer, making data efficient, secure, and ready for scale.
We eliminate the hidden inefficiencies in modern data platforms—slashing storage and compute costs, accelerating pipelines, and boosting platform efficiency. The result: 60%+ lower storage costs, up to 60% lower compute spend, 3× faster data processing, and 20% overall efficiency gains.
Massive data should fuel innovation, not drain budgets. We remove the bottlenecks holding AI and analytics back—making data lighter, faster, and smarter so teams can ship breakthroughs, not babysit storage and compute bills.
What You’ll Do
Lead and build a team of 8–10 engineers shipping core platform services across the AI data stack
Stay 40% hands-on in high-leverage areas like Spark shuffles, Iceberg metadata stores, and vectorized engines
Translate research into production—owning the path from prototype to hardened, planet-scale systems
Coach architecture & velocity—drive weekly iteration while enforcing engineering excellence
Instill a culture of rigor—from RFCs and code reviews to latency regression tracking and post-mortems that teach
Own quarterly outcomes—measuring success through performance (P90 latency), reliability (4+ nines), and hiring bar (zero-regret additions)
Design for scale & autonomy—build workflows where two-pizza teams can ship daily with minimal friction
Attract and grow top talent—recruit 10x builders and create an environment of psychological safety and learning
What We’re Looking For
7+ years in backend or infra engineering roles, with 2+ years as a tech lead or manager
Proven success building and leading high-caliber teams in performance-critical environments (e.g. databases, ML infra, lakehouse systems)
Deep experience with distributed compute frameworks (Spark, Trino, Presto) and columnar storage formats (Parquet, ORC)
Familiarity with Iceberg or Delta Lake internals
Strong system design instincts and ability to guide teams through trade-offs
Track record of balancing hands-on execution with leadership, mentorship, and delivery
Passion for building foundational technology that changes how data is used at scale
Why Join Granica
Core Differentiation: We’re focused on unlocking a deeper layer of AI infrastructure. By optimizing the way data is stored, processed, and retrieved, we make platforms like Snowflake and Databricks faster, more cost-efficient, and more AI-native. Our work sits at the most fundamental layer of the AI stack: where raw data becomes usable intelligence.
Elite peers—you’ll collaborate with engineers from Meta, Google, Databricks, Okta, and early FAANG builders
Clear metrics, real impact—our platform cuts storage costs 60%, compute 60%, and boosts processing speeds 3x
Unusually high leverage—no bloat, minimal hierarchy, and high ownership from day one
Long-term alignment—backed by top-tier investors and built for technical founders and builders
Compensation & Benefits
Competitive salary and equity
Premium healthcare, vision, and dental
Flexible hybrid work setup (Mountain View HQ)
Unlimited PTO + quarterly recharge days
Stipends for learning, publishing, or open-source engagement
Equal Opportunity: Granica is an equal opportunity employer. We’re committed to building a diverse, inclusive team and encourage candidates from all backgrounds to apply.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
IT Services and IT Consulting
#J-18808-Ljbffr
Candidates should take the time to read all the elements of this job advert carefully Please make your application promptly. Join to apply for the
Engineering Manager
role at
Agilesoft .
Granica is redefining how enterprises prepare and optimize data at the most fundamental layer of the AI stack—where raw information becomes usable intelligence. Our technology operates deep in the data infrastructure layer, making data efficient, secure, and ready for scale.
We eliminate the hidden inefficiencies in modern data platforms—slashing storage and compute costs, accelerating pipelines, and boosting platform efficiency. The result: 60%+ lower storage costs, up to 60% lower compute spend, 3× faster data processing, and 20% overall efficiency gains.
Massive data should fuel innovation, not drain budgets. We remove the bottlenecks holding AI and analytics back—making data lighter, faster, and smarter so teams can ship breakthroughs, not babysit storage and compute bills.
What You’ll Do
Lead and build a team of 8–10 engineers shipping core platform services across the AI data stack
Stay 40% hands-on in high-leverage areas like Spark shuffles, Iceberg metadata stores, and vectorized engines
Translate research into production—owning the path from prototype to hardened, planet-scale systems
Coach architecture & velocity—drive weekly iteration while enforcing engineering excellence
Instill a culture of rigor—from RFCs and code reviews to latency regression tracking and post-mortems that teach
Own quarterly outcomes—measuring success through performance (P90 latency), reliability (4+ nines), and hiring bar (zero-regret additions)
Design for scale & autonomy—build workflows where two-pizza teams can ship daily with minimal friction
Attract and grow top talent—recruit 10x builders and create an environment of psychological safety and learning
What We’re Looking For
7+ years in backend or infra engineering roles, with 2+ years as a tech lead or manager
Proven success building and leading high-caliber teams in performance-critical environments (e.g. databases, ML infra, lakehouse systems)
Deep experience with distributed compute frameworks (Spark, Trino, Presto) and columnar storage formats (Parquet, ORC)
Familiarity with Iceberg or Delta Lake internals
Strong system design instincts and ability to guide teams through trade-offs
Track record of balancing hands-on execution with leadership, mentorship, and delivery
Passion for building foundational technology that changes how data is used at scale
Why Join Granica
Core Differentiation: We’re focused on unlocking a deeper layer of AI infrastructure. By optimizing the way data is stored, processed, and retrieved, we make platforms like Snowflake and Databricks faster, more cost-efficient, and more AI-native. Our work sits at the most fundamental layer of the AI stack: where raw data becomes usable intelligence.
Elite peers—you’ll collaborate with engineers from Meta, Google, Databricks, Okta, and early FAANG builders
Clear metrics, real impact—our platform cuts storage costs 60%, compute 60%, and boosts processing speeds 3x
Unusually high leverage—no bloat, minimal hierarchy, and high ownership from day one
Long-term alignment—backed by top-tier investors and built for technical founders and builders
Compensation & Benefits
Competitive salary and equity
Premium healthcare, vision, and dental
Flexible hybrid work setup (Mountain View HQ)
Unlimited PTO + quarterly recharge days
Stipends for learning, publishing, or open-source engagement
Equal Opportunity: Granica is an equal opportunity employer. We’re committed to building a diverse, inclusive team and encourage candidates from all backgrounds to apply.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
IT Services and IT Consulting
#J-18808-Ljbffr