Position Overview 

The RAN Deployment Engineer is responsible for executing all deployment, installation, and integration activities required to enable stable satellite‑to‑mobile connectivity across India and within global delivery programs. This role supports gateway and cell‑site builds, performs beam surveys, validates field installations, uploads configurations, and conducts probe‑based integration checks to ensure RAN readiness for satellite network activation. 

The position works closely with regional engineering teams, the NOC, vendors, and global deployment groups to resolve technical blockers, uphold high integration quality, and support seamless service enablement. 

Operating at the intersection of field engineering and advanced satellite‑RAN deployment, this role demands precision during installation, disciplined validation practices, and continuous coordination with cross‑functional teams. The RAN Deployment Engineer must balance technical accuracy, operational urgency, and regulatory variations across India to ensure smooth and consistent readiness for global satellite network activation.

Key Responsibilities 

Field Deployment & Installation Activities 

• Deliver RAN deployment activities including cell‑site builds, managing end-to-end field installation processes for satellite-RAN infrastructure 

• Execute installation checks and commissioning procedures to validate proper equipment mounting, cabling, power connections, and environmental controls 

• Validate CIQ inputs/outputs and CIQ-to-SCF generation to avoid deployment rework 

• Validate Cell site router to Core integration, transport readiness 

• Perform configuration uploads and software provisioning to ensure RAN equipment is properly configured according to deployment specifications 

• Perform and validate BPMS to eNB port mapping, transport, clocking, and interface readiness 

• Support Beam Go / No-Go readiness reviews and provide technical sign-off inputs 

• Own technical handover from Delivery to Service Acceptance, ensuring all acceptance criteria and artifacts are met 

• Enable stable satellite‑mobile connectivity through systematic installation, integration, and validation of RAN components and interfaces 

Technical Validation & Testing 

• Perform probe validations and acceptance testing to verify RAN functionality, connectivity, and performance against established criteria 

• Conduct integration testing between satellite-RAN equipment and terrestrial network components to ensure seamless connectivity 

• Execute acceptance tasks including functional testing, performance validation, and documentation completion for site commissioning 

• Execute Acceptance checks with vendors for handover to Service Acceptance 

Coordination & Collaboration 

• Coordinate with regional engineering, NOC, vendors, and global deployment teams to align deployment activities with project schedules and technical requirements 

• Interface with network operations centres to ensure proper monitoring integration and operational readiness during deployment phases 

• Work with vendor teams to resolve equipment issues, on site hardware delivery, coordinate software updates, and ensure proper installation procedures 

• Collaborate with global deployment teams to maintain consistency in deployment standards and share lessons learned across regions 

Technical Issue Resolution & Quality Assurance 

• Resolve technical blockers encountered during deployment including equipment failures, configuration issues, and integration challenges 

• Troubleshoot complex technical problems affecting RAN performance, connectivity, or functionality during installation and commissioning 

• Ensure reliable RAN readiness supporting global satellite network activation through comprehensive validation and quality assurance processes 

• Document and escalate unresolved issues to appropriate technical teams while implementing temporary workarounds to maintain deployment schedules  

Qualifications  

Education 

• Bachelor's degree in electrical engineering, telecommunications engineering, computer engineering, or related technical field 

• Associate degree with relevant telecommunications experience accepted  

Experience 

• Minimum 4+ years in telecommunications field deployment, network installation, or wireless infrastructure commissioning 

• 2+ years hands-on experience with RAN deployment, cell site installation, or wireless network infrastructure and CIQ handling 

• Proven experience with field installation, testing, and commissioning of complex telecommunications equipment  

Required Technical Expertise 

• Strong understanding of RAN technologies, wireless communications principles, and telecommunications infrastructure 

• Knowledge of installation procedures for telecommunications equipment including Rack, eNodeB antennas, transceivers, GPS & CSR and network infrastructure 

• Familiarity with configuration management, software provisioning, and equipment commissioning processes  

Preferred Qualifications 

• Experience with satellite communications systems, satellite-RAN integration, or space-terrestrial network deployment 

• Background in field deployment roles at wireless carriers, equipment vendors, or telecommunications contractors 

• Knowledge of safety procedures and compliance requirements for telecommunications field work 

• Experience with network monitoring systems and performance validation tools 

• Familiarity with project coordination and deployment management practices  

Professional Skills 

• Strong problem-solving and troubleshooting skills for complex technical issues in field environments 

• Excellent communication skills for coordination with multiple technical teams and stakeholders 

• Proven ability to work independently in field environments while maintaining safety and quality standards 

• Experience with technical documentation, test reporting, and deployment validation procedures  

Technology Proficiency 

• Proficiency with RF testing equipment including spectrum analysers, power meters 

• Experience with network configuration tools and equipment management systems 

• Familiarity with field measurement software and data collection tools used in wireless deployment 

• Knowledge of safety equipment and procedures required for telecommunications field work  

Skills & Competencies 

• Field Installation Expertise: Hands-on experience with telecommunications equipment installation, cabling, and commissioning procedures 

• RF Testing & Validation: Proficiency with RF measurement equipment and wireless network performance validation techniques 

• Technical Troubleshooting: Systematic approach to identifying and resolving complex technical issues in field environments 

• Safety Consciousness: Commitment to safety procedures and compliance with telecommunications industry safety standards 

• Documentation & Reporting: Clear technical writing and accurate documentation of deployment activities and test results 

• Team Coordination: Effective collaboration across multiple technical disciplines and organizational boundaries  

Cross-Functional Interfaces 

This role collaborates regularly with: 

• Internal: Regional Engineering Teams, Network Operations Center, RF Engineering, Field Operations, Quality Assurance, Program Management, Safety and Compliance 

• External: Equipment vendors, installation contractors, testing laboratories, site owners, local regulatory authorities  

Physical Requirements 

• Role will be based in United States with extensive travel for field deployment activities across multiple regions (~50%) 

• Ability to perform physical field work including equipment installation,  

• Valid driver's license and ability to travel to remote deployment sites as required by project schedules 

• Ability to work flexible hours including weekends and extended shifts during critical deployment phases 

This job description may not be inclusive to the duties and responsibilities listed. Additional tasks may be assigned to the employee from time to time or the scope of the job may change as needed by business demands. 

Who We Are 

Core Scientific is a leading provider of infrastructure for high-performance compute in North America. Our mission is to accelerate digital innovation by scaling high-value compute rapidly, efficiently, and responsibly.  We transform energy into high-value compute with unmatched efficiency at scale. The company is a $5 billion publicly traded company (NASDAQ: CORZ). 

We power AI, HPC, and other next-generation data center workloads demanding exceptional computing power, in addition to our digital asset mining operations.  We own and operate nine data centers in seven states, housing advanced infrastructure for our customers. 

What sets us apart? We have an entrepreneurial culture, a "can-do" and collaborative attitude, and we own and control our infrastructure. These strategic advantages enable us to maintain operational excellence, increase efficiency, and rapidly deploy cutting-edge innovations developed by our team of experts. 

Join us and accelerate your career alongside our groundbreaking journey. We seek smart, creative, and collaborative professionals who thrive in a fast-paced, result-driven environment. Ready to be part of something exceptional? Apply today and make an impact at Core Scientific. 

Title 

Enterprise Architect 

Reports To 

Chief Technology Officer 

The Job 

As organizations scale, digital systems outpace the assumptions that shaped them. Permissions accumulate, automation compounds, reconciliation logic ages, and integrations drift until policy and documentation alone can no longer ensure that system behavior reflects operational, financial, and revenue-generating reality. 

We are seeking an Enterprise Architect within the Technology organization to ensure that enterprise systems operate with durable precision as complexity increases. The mandate is dual: contain structural risk and harden the enterprise into a disciplined, programmatic system that accelerates revenue, efficiency, and enterprise value. Reporting to the Chief Technology Officer and operating across engineering, data, finance, and operations, this role carries executive sponsorship aligned with CEO directive to strengthen institutional precision so that technology compounds advantage rather than complexity. 

Digital systems define operational truth and revenue execution. When architecture diverges from real-world behavior, inefficiency compounds quietly, throughput slows, reporting distorts, and value erodes. This role engineers durability directly into system design—strengthening control architecture, validating behavior, eliminating operational debt, and maintaining disciplined access models so efficiency becomes structural rather than dependent on vigilance. 

Success is measured by increasing precision at scale. Systems align with operational and financial reality without constant intervention, weaknesses are surfaced before they compound, automation reinforces accountability rather than obscuring it, and improvements in control architecture translate into faster decision velocity, cleaner financial signal, reduced workflow friction, and measurable performance gains. Hardening removes fragility without introducing bureaucracy; precision increases speed. 

This is not a compliance or audit function. It is a high-trust, senior individual contributor role embedded within live enterprise systems with direct access to the CTO and visibility aligned with CEO mandate. 

Responsibilities 

• Investigate enterprise systems to ensure that digital workflows reflect operational, financial, and revenue-generating reality. 

• Map control surfaces across ERP, CRM, data pipelines, automation frameworks, APIs, and integrations, identifying structural weaknesses or inefficiencies.  

• Analyze reconciliation logic embedded within tooling and validate that assumptions remain sound under current scale and transaction velocity. 

• Detect privilege creep, access model drift, override frequency, structural permission risk, and hidden inefficiencies embedded in nuisance technology. 

• Examine automation layers for masked control failures, redundant workflows, and process friction that suppress throughput. 

• Redesign or reinforce enterprise control frameworks where necessary, strengthening architecture without introducing bureaucratic drag. 

• Use structured data analysis, scripting, and AI-accelerated investigative workflows to surface anomalies, quantify exposure, and model performance impact. 

• Translate technical findings into executive-level analysis that connects control integrity to margin protection, decision velocity, and revenue acceleration. 

• Partner with engineering and operations leaders to eliminate structural inefficiencies and convert fragile workflows into hardened programs. 

• Strengthen traceability, documentation, and institutional memory so that system durability scales with growth. 

• Foster open, respectful, and professional communication directly within the team as well as with co-workers/ teammates and leaders across the organization 

• Performs other duties as assigned 

Qualifications 

We are intentionally open to unconventional backgrounds. Exceptional candidates may have experience as: 

• A senior technical leader responsible for building and hardening systems under pressure. 

• A systems engineer or platform architect who has diagnosed and repaired structural fragility. 

• A forensic or investigative professional with strong technical depth. 

• A security or controls engineer with enterprise exposure. 

• A senior operator who has eliminated operational debt while scaling performance. 

You are likely a solution-oriented operator who derives energy from untangling nuisance technology, cleaning up degraded workflows, and eliminating inefficiencies that others tolerate. 

• Think in systems and control surfaces rather than isolated incidents. 

• Understand that structural failure often begins as unmanaged drift. 

• Recognize operational debt embedded in tooling and process before it becomes material loss. 

• Are materially focused and capable of distinguishing signal from noise. 

• Remain calm and precise in ambiguous environments. 

• Are comfortable operating without formal signature authority. 

• Can interrogate systems without destabilizing trust. 

• Thrive on turning fragility into engineered durability. 

• Prefer building hardened programs over writing policies. 

AI proficiency is foundational in this role. You are expected to use AI as a primary analytical engine, a bridging mechanism between systems, and a general-purpose accelerator for investigation, modeling, and solution design. This includes building repeatable AI-assisted workflows that combine data extraction, anomaly detection, hypothesis testing, and structured reporting. 

• Querying structured data using SQL or similar tools. 

• Writing lightweight scripts in languages such as Python to validate assumptions and test system behavior. 

• Navigating APIs, integration layers, automation frameworks, and permission hierarchies. 

• Using AI to synthesize findings, stress-test logic, generate diagnostic artifacts, and accelerate technical validation. 

• Distinguishing between superficial AI usage and disciplined, reproducible AI-driven system interrogation. 

You do not need to be a full-time software engineer. However, you must be technically literate enough to move beyond dashboards and into underlying system logic, and disciplined enough to operationalize AI into repeatable investigative infrastructure. 

Location 

Austin, TX or Miami, FL. While proximity to our core offices is preferred, we prioritize capability and alignment with mandate and will consider remote candidates where appropriate. 

Travel 

Occasional travel will be required up to 25%. 

Work Environment 

This job typically operates in a professional office environment and routinely utilizes standard equipment, including laptop computers and smartphones. This role will also travel to data center sites and the work environment at a data center may contain loud noise, construction and other operational elements,  

Physical Demands 

While performing the duties of this job, the employee is frequently required to sit, stand, walk, use hands, and lift up to 25 pounds.   

Position Type/ Expected Hours of Work 

This is a full-time position. General hours and days of work are Monday through Friday, 8:00 a.m. to 5:00 p.m. Some nights and weekends may be required. 

Supervisory Experience (Yes or No) 

No 

About Nubank

Nu is one of the largest digital financial platforms in the world, with more than 127 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America and this is still just the beginning of the purple future we're building.

Listed on the New York Stock Exchange (NYSE: NU), we combine proprietary technology, data intelligence, and an efficient operating model to deliver financial products that are simple, accessible, and human.

Our impact has been recognized by global rankings such as Time 100 Companies, Fast Company's Most Innovative Companies, and Forbes World's Best Bank. Visit our institutional page https://international.nubank.com.br/careers/

About the role

AI is core to how Nubank builds products — and securing it is one of the most critical and forward-looking challenges in the company. The AI Security team, part of Nubank's Information Technology & Security area, is responsible for ensuring that AI systems are developed and operated safely and securely at scale, across LLM-powered applications, autonomous agents, and the infrastructure that supports them.

As Lead Security Engineer (AI), you will own and drive Nubank's defensive security strategy for AI products and internal tools. You will define frameworks, set technical direction, build runtime protections, and enable engineering teams across the company to ship AI systems securely by default. This role sits at the intersection of cutting-edge AI and high-stakes security — and your work will directly shape how one of the world's largest fintechs builds trustworthy AI at scale.

You'll be Responsible For

• Leading the security strategy for Nubank's AI systems — covering LLM-powered applications, AI agents, and their underlying infrastructure — and building the standards and frameworks that guide secure AI deployment across the company.
• Securing AI agents and autonomous workflows by hardening tool usage, enforcing appropriate permission levels, and monitoring agent behavior and decision-making in production.
• Designing and enabling secure architectural patterns for AI applications, including LLM-based services and agent orchestration systems.
• Developing AI-specific detection and monitoring capabilities to identify abuse, misuse, and anomalous behavior — including telemetry across prompts, responses, tool usage, and agent execution.
• Designing and implementing runtime protections for LLM applications, such as prompt injection detection, jailbreak protection, abuse detection, and output safety controls.
• Collaborating with AI engineers and platform teams to integrate security controls into AI development and deployment pipelines.
• Staying current with emerging threats and AI security trends, translating them into concrete controls, guidelines, and standards across Nubank's engineering organization.

We Are Looking for a Person Who Has

• Deep expertise in product security, application security, or cloud security, combined with hands-on experience building AI agent systems.
• A proven track record leading cross-team technical initiatives — setting standards and driving adoption without direct authority.
• Experience designing and implementing secure systems and controls in production environments.
• Hands-on experience with runtime security controls (input validation, abuse detection, policy enforcement) in high-throughput production systems.
• Solid familiarity with LLM application architectures — including prompt pipelines, tool use, and RAG — and their threat surfaces such as prompt injection, data exfiltration, and jailbreaks.
• Strong understanding of agentic systems and AI infrastructure, with the ability to threat-model novel and non-deterministic systems.
• Experience building monitoring, telemetry, and alerting for production systems.
• Strong programming skills in at least one production language, with the ability to read and review code across the AI stack.

Location

• Durham, United States
• Miami, United States
• Palo Alto, United States
• Washington DC, United States

Our Benefits

• Opportunity of earning equity at Nu
• Medical Insurance
• Dental and Vision Insurance
• Life Insurance and AD&D
• Extended maternity and paternity leaves 
• Nucleo - Our learning platform of courses
• NuLanguage - Our language learning program
• NuCare - Our mental health and wellness assistance program
• 401K
• Saving Plans - Health Saving Account and Flexible Spending Account
• Work-from-home Allowance
• Relocation Assistance Package, if applicable.

Work Model for this Role

Hybrid 2–3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/

Location-Specific Disclosures

• Palo Alto: Total compensation includes base salary, RSUs and benefits. Base salary range: $15,360 - $23,040

ABOUT THE WORK ENVIRONMENT

This role is in office at our corporate headquarters in the Brickell area of Miami, Florida. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

About Us

Nu is one of the largest digital financial platforms in the world, with more than 127 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America and this is still just the beginning of the purple future we're building.

Listed on the New York Stock Exchange (NYSE: NU), we combine proprietary technology, data intelligence, and an efficient operating model to deliver financial products that are simple, accessible, and human.

Our impact has been recognized by global rankings such as Time 100 Companies, Fast Company's Most Innovative Companies, and Forbes World's Best Bank. Visit our institutional page [Careers at Nu - Join our team!](https://international.nubank.com.br/careers/)

About the Role

At Nu, data is the foundation that powers our AI and machine learning models, enabling millions of customers to access fair financial products. As a Machine Learning Engineer in AI Core, Data Intelligence, you’ll work across a broad spectrum — from building scalable data infrastructure and feature pipelines that feed our state-of-the-art foundation models to designing, training, and shipping transaction classification models that power critical customer experiences across the company.

You'll work at the intersection of data and applied machine learning, contributing across multiple stages of the ML lifecycle: ingesting and labeling data, training and evaluating models, and helping with deployment and production monitoring through robust quality controls. You’ll partner closely with product, compliance, and ML teams to ensure models are auditable, privacy-aware, and deliver measurable business value.

You'll join a team that manages the data engineering backbone of AI Core, ensuring data is accessible, healthy, and properly tracked across our entire ML ecosystem. Here, you'll combine your expertise in building scalable data systems with your passion for machine learning, creating solutions that enable our models to learn from better, richer data.

You can read more about the work in the AI Core team on our blog: https://building.nubank.com/understanding-our-customers-finances-through-foundation-models/

Key Responsibilities

As a Lead Machine Learning Engineer in AI Core Data Intelligence, you will:

• Design and build scalable data ingestion pipelines that bring new datasets into our AI Core platform, ensuring reliable, efficient data flow from source to model training.
• Implement data quality monitoring and validation systems that catch issues before they impact model performance, maintaining the health of datasets across our ML ecosystem.
• Model new types of data into our foundation models.
• Analyze the impact of new data sources on existing models, conducting experiments to measure performance improvements and guide data acquisition decisions.
• Develop and maintain data preparation workflows that transform raw data into features ready for model training, working with distributed computing frameworks like Ray.
• Tune and optimize machine learning models when new datasets are integrated, applying hyperparameter optimization and evaluating model performance improvements.
• Collaborate with AI Core ML, Platform, and Infra teams to ensure seamless data flow across our ML infrastructure, from ingestion to model deployment.
• Lead technical initiatives that improve our data engineering practices, setting standards for data quality, pipeline reliability, and model-data integration.
• Mentor team members and contribute to hiring activities, helping build a strong and diverse team that drives innovation in AI infrastructure.

Basic Qualifications

• Typically 6+ years of experience in machine learning engineering, data engineering, or related fields with a strong track record of building production data and ML systems.
• Proven experience designing and building data ingestion pipelines at scale, with expertise in distributed computing frameworks (Ray, Spark, or similar).
• Strong background in applied machine learning, including model training, hyperparameter tuning, and performance evaluation.
• Experience analyzing how data changes impact model performance, with the ability to design and run experiments to measure improvements.
• Proficiency in Python for data engineering and ML workflows, with experience working with large-scale data processing systems.
• Solid understanding of data quality principles and experience implementing monitoring, validation, and alerting systems.
• Strong problem-solving skills with the ability to address complex, ambiguous problems requiring coordination across multiple teams.
• Excellent communication skills, capable of explaining technical concepts to both technical and non-technical stakeholders.
• Demonstrated leadership experience, including mentoring team members and contributing to technical decision-making.

Preferred Qualifications

• Experience with MLflow or similar model tracking and versioning systems.
• Knowledge of foundation models, fine-tuning workflows, and transformer architectures.
• Experience with data pipeline orchestration tools (Dagster, Airflow, or similar).
• Background in financial services or fintech, understanding the unique data challenges in this domain.
• Experience working in a fast-paced, high-growth environment with distributed teams.
• Track record of reducing complexity in data systems and improving developer experience for ML teams.
  
  

Our Benefits

• Opportunity of earning equity at Nu
• Medical Insurance
• Dental and Vision Insurance
• Life Insurance and AD&D
• Extended maternity and paternity leaves 
• Nucleo - Our learning platform of courses
• NuLanguage - Our language learning program
• NuCare - Our mental health and wellness assistance program
• Extended maternity and paternity leaves 
• 401K
• Saving Plans - Health Saving Account and Flexible Spending Account
• Work-from-home Allowance
• Relocation Assistance Package, if applicable.

Work Model for this Role

Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/

Locations: This role is available in any of our North American offices (Palo Alto, USA; Miami, USA; Durham, USA; Toronto, CAN)