13 ΡΠ°ΡΠΎΠ² Π½Π°Π·Π°Π΄
Distinguished Systems Developer (SQL Engine)
144Β 000 - 205Β 000$
ΠΡΡΡ & Π‘ΠΎΠΏΡΠΎΠ²ΠΎΠ΄
ΠΠ»Ρ ΠΌΡΡΡΠ° Ρ ΡΡΠΎΠΉ Π²Π°ΠΊΠ°Π½ΡΠΈΠ΅ΠΉ Π½ΡΠΆΠ΅Π½ Plus
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
Π’Π΅ΠΊΡΡ:
TL;DR
Distinguished Systems Developer (SQL Engine) (SQL, multi-model data, AI): Building next-generation query processing and execution engines for petabyte-scale analytics and AI-native workloads with an accent on query optimization, compiler-accelerated storage access, and vectorized execution. Focus on designing adaptive execution strategies, integrating multi-model indexing and caching, and enabling vector search, graph traversal, and probabilistic joins through SQL.
Location: Boston, MA, United States
Salary: $144,000β$205,000 USD per year, plus a discretionary annual variable target incentive.
Company
develops data platforms for healthcare, finance, manufacturing, and supply chain customers in more than 80 countries.
What you will do
- Architect and implement query optimization and execution components that scale across petabytes.
- Build query parsing, validation, transformation, plan generation, adaptive execution, code generation, and vectorized execution capabilities.
- Design data processing abstractions and execution engines for SQL, JSON, vector search, graph traversal, and probabilistic joins.
- Integrate the SQL Engine with multi-model storage, indexing, and caching strategies.
- Develop programmable data pipelines that improve downstream ML model performance.
- Mentor engineers, guide technical discussions, and influence long-term system architecture.
Requirements
- 10+ years of experience in systems-level or database internals engineering.
- Expertise in SQL query engines, optimizers, execution runtimes, or data compiler toolchains.
- Experience with multi-model data systems, including SQL, JSON, vector search, or graph traversal.
- Expertise in at least one systems programming language or LLVM-based code generation environment.
- Strong knowledge of relational algebra, compiler construction, and data-intensive workloads.
- Passion for balancing performance, correctness, and usability; ability to evaluate and verify AI-generated outputs.
Nice to have
- Experience with AI infrastructure or ML inference pipelines.
- PhD degree or published research experience.
- Experience designing and implementing AI-augmented engineering workflows.
Culture & Benefits
- Innovation, prototyping, technical ownership, and long-term architectural thinking are encouraged.
- Cross-domain collaboration spans storage, processing, and AI systems.
- Work environment emphasizes deep focus, quality, technical rigor, and sustainable pace.
- Medical, vision, and dental insurance, plus short- and long-term disability and life insurance.
- 401(k) profit-sharing contribution, paid time off, holidays, parental leave, and tuition reimbursement.
ΠΡΠ΄ΡΡΠ΅ ΠΎΡΡΠΎΡΠΎΠΆΠ½Ρ: Π΅ΡΠ»ΠΈ ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Ρ ΠΏΡΠΎΡΠΈΡ Π²ΠΎΠΉΡΠΈ Π² ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ iCloud/Google, ΠΏΡΠΈΡΠ»Π°ΡΡ ΠΊΠΎΠ΄/ΠΏΠ°ΡΠΎΠ»Ρ, Π·Π°ΠΏΡΡΡΠΈΡΡ ΠΊΠΎΠ΄/ΠΠ, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡΠ΅ ΡΡΠΎΠ³ΠΎ - ΡΡΠΎ ΠΌΠΎΡΠ΅Π½Π½ΠΈΠΊΠΈ. ΠΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΆΠΌΠΈΡΠ΅ "ΠΠΎΠΆΠ°Π»ΠΎΠ²Π°ΡΡΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡΠΈΡΠ΅ Π² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β