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Requirements:
5+ years of senior IC engineering experience
Strong systems instincts and a quality bar that survives moving fast
Production experience with cloud platforms (AWS, GCP, or Azure)
Comfort across the stack - language proficiency matters less than judgment
Bonus
AI/ML infrastructure or LLM-product engineering experience
Vector or graph database experience
Frontend craft (React/Next.js, design-system contribution)
Construction or AEC exposure

Requirements:
Strong DevOps/platform/SRE experience at a company with a real engineering culture (FAANG, unicorn, or a well-established startup with high standards)
Deep Kubernetes and AWS - you have architected, scaled, and debugged production clusters, not just deployed to them
Infrastructure as code in your bones - Terraform or equivalent, with strong opinions on reproducibility and auditability
CI/CD ownership - you have built pipelines that engineers trust and rarely think about
Production observability and incident response at meaningful scale
Comfort with and curiosity about AI/LLM workloads. We are an AI-native company; you should be using AI in how you work, and excited to operate the infrastructure agents run on

Requirements:
* Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
* At least 8 years of proven hands-on experience managing or working directly with data center and IT infrastructure (compute, networking, SAN/NAS, replication, backup/recovery, or similar).
* 5+ years of relevant product management experience, ideally in enterprise storage or infrastructure.
* Strong ability to translate complex technical and business challenges, and bring deep customer and business insight to product decisions, with a solid grasp of the needs of enterprise customers and service providers.
* Demonstrated experience collaborating with enterprise clients and large-scale accounts to deliver product releases and support successful deployments.
* Demonstrated initiative and self-motivation, with a track record of taking full ownership of projects from start to finish while requiring minimal guidance.
* Outstanding written and verbal communication skills, effective in both technical and business conversations. Ways to Stand Out:
* MBA or advanced technical degree.
* Prior experience at a storage or infrastructure vendor (Dell/EMC, NetApp, Pure, Vast, DDN, etc.).
* Experience partnering with global, enterprise-scale customers on infrastructure or data platform deployments, leading POCs, and beta programs.
* History of succeeding in product management within international or cross-cultural organizations.
About infinidat Infinidat’s enterprise storage portfolio provides global Fortune 500 enterprises and service providers with best-in-class solutions for primary storage, next-generation data protection, disaster recovery, business continuity, and cyber resilience. Infinidat’s acclaimed InfuzeOS is the one of the most flexible and complete enterprise software-defined storage architectures in the industry. We recently announced powerful enhancements, an extensive expansion, and the dynamic evolution of our award-winning G4 enterprise cyber and AI storage solutions! Not only did Infinidat win over 40 awards in 2025 , but was named a Gartner® Peer Insights™ Voice of the Customer Award for Primary Storage for the 7th time!

Requirements:
Spark at scale- You have tuned real Spark jobs for performance and cost - skew, shuffle, partitioning, memory, spill - run pipelines over TB-scale or billions of rows in production, and can reason about the physical execution plan, not just write DataFrame code.
5+ years of professional experience building and owning production systems.
Strong Python and SQL, with maintainable, tested production code.
Strong software engineering fundamentals across the stack. You can own backend services and pick up frontend when the work needs it - not a pipelines-only specialist.
AI-first way of working- You build with AI in your day-to-day development, using it to move faster and raise the quality of what you ship.
Deep experience designing and operating ETL/ELT pipelines, data models, and distributed data-processing systems.
Comfortable advising and pairing with other engineers and data scientists on data work.
Strong AWS experience: S3, Glue, EMR, Athena, and related compute and orchestration services.
Experience with modern data lakehouse or warehouse architectures. Apache Iceberg is a strong advantage.
Experience with workflow orchestration (Airflow or similar), CI/CD, Docker, Git, and infrastructure as code such as AWS CDK and CloudFormation.
Strong understanding of data quality, schema evolution, lineage, observability, privacy, security, and access controls. Experience with regulated or sensitive data, such as healthcare / PHI, is an advantage.
High comfort in a fast-moving environment with incomplete requirements, high ownership, and a strong sense of urgency.

Requirements:
5+ years in product, with a strong track record on AI or technically-deep products
Real conviction about being grounded in users - not personas
Ability to write clearly and decide quickly
Curiosity about industries you don't yet understand
Bonus
Construction or vertical-software background
Experience shaping a product practice from scratch

Requirements:
Strong engineering background with senior-IC experience
Ability to translate ambiguous customer needs into technical implementation
Comfort in front of senior buyers and on active job sites
A real interest in customers - not just a polite tolerance
Bonus
AEC, construction, or vertical-software exposure
Solutions-engineering or forward-deployed background
Experience shaping a customer-facing engineering practice from scratch

Requirements:
6+ years of product design experience, including senior IC work on technical products
A portfolio that shows real craft and a real point of view
Comfort working closely with engineering and AI research
Confidence picking up a new domain - construction - and learning it deeply
Bonus
Experience designing for technical or vertical industries
Design-system architecture experience
Familiarity with AI-native interaction patterns

Requirements:
6+ years of product design experience, including senior IC work on technical products
A portfolio that shows real craft and a real point of view
Comfort working closely with engineering and AI research
Confidence picking up a new domain - construction - and learning it deeply
Bonus
Experience designing for technical or vertical industries
Design-system architecture experience
Familiarity with AI-native interaction patterns

Requirements:
What you'll need:
7+ years of production backend or data infrastructure experience.
Excellent teamwork and communication skills, with a demonstrated ability to explain complex systems and facilitate collaborative solutions.
Deep experience with stream processing systems (Flink, Kafka, or equivalents) at production scale, including failure modes, recovery, and operational burden.
Strong distributed systems instincts: you think about correctness and reliability before you think about features.
Experience with data quality or observability infrastructure. You've built or owned the systems that keep a data platform honest.
Internal product mindset: you treat the teams you serve as customers and make deliberate choices about what to build vs. what not to build.

It'd be really cool if you also:
Have worked with data contracts, schema registries, or data governance tooling.
Have experience with JVM languages (Scala, Java, Kotlin) and big data DBs (Aerospike/elasticsearch/etc).
Have contributed to agentic or LLM-adjacent infrastructure. You understand what "data quality for agents" actually means in practice.
Have operated at a team technical anchor level in a small, high-scope team where breadth of ownership is the norm.

Requirements:
Technological degree or diploma, or a strong technical background
2-4 years of relevant sales experience
Proven experience managing technology-related projects
Excellent English communication skills, both written and spoken
Strong motivation and a genuine drive to succeed in sales
Familiarity with electrical systems and power-related technologies - a significant advantage
Experience working with the defense industry - a significant advantage

Requirements:
M.Sc. or Ph.D. in aerospace or mechanical engineering, acoustics, or physics, with a focus on aeroacoustics or noise control.
4+ years of hands-on aeroacoustics work - rotorcraft, propellers, fans, turbomachinery, or airframe noise - in industry or applied research.
Proven experience running acoustic test campaigns: microphone arrays, beamforming, anechoic or wind tunnel measurements, and full calibration traceability.
Strong acoustic signal processing skills - spectral analysis, order tracking, de-Dopplerization, coherence-based source separation - implemented in Python or MATLAB.
Working command of source-noise prediction methods (Ffowcs Williams-Hawkings, semi-empirical broadband models such as BPM, or equivalent) and a clear-eyed view of their limits.
Fluency in community and certification noise metrics - EPNL, SEL, dBA - and the measurement procedures behind ICAO Annex 16 / 14 CFR Part 36 style testing.
Demonstrated ability to own a question end to end: from test plan to instrumented rig to a conclusion you would defend in front of the whole company.

Requirements:
Strong background in modern ML - LLMs, retrieval, agent systems
Experience shipping AI to production, not just notebooks
Comfort with messy, document-heavy domains
A real interest in evaluation as a discipline, not an afterthought
Bonus
Published work on agents, retrieval, or evaluation
Experience with vision-language models on document or technical-drawing data
Construction or AEC industry exposure

Requirements:
B.Sc. or higher in Electrical Engineering
At least 5-7 years of proven experience in board-level hardware design, including analog, digital, and power electronics
Experience in hardware and firmware integration
Hands-on experience with professional schematic, PCB design, simulation, and verification tools
Experience using analysis tools to simulate and validate analog, power, and mixed-signal circuits
Strong experience in board bring-up, laboratory measurements, validation, and debugging
Practical experience with oscilloscopes, analyzers, electronic loads, and other laboratory equipment
Hands-on experience with PCB manufacturing and assembly processes, including work with external PCB and PCBA suppliers
Experience in component engineering, BOM management, substitute components, and supply-chain constraints
Excellent written and spoken English
Significant advantages
Experience designing power electronics or motion control systems
Experience with thermal analysis and heat-simulation tools
Knowledge and practical experience with EMC/EMI requirements and relevant standards
Experience designing hardware for defense, aerospace, robotics, drones, or other mission-critical applications