(Senior) Java Developer (Staking)

I am Sadr, CEO of Oferli. We are building a high-performance, elite technical team, and I am looking for 5 to 10 dedicated founding technical partners to join me in this mission.
​The Vision:
Oferli is a 100% decentralized ecosystem. While we are rooted in Web3, our expertise spans across professional web and mobile application development. We are not just another agency; we are crafting the next generation of digital solutions. Our goal is to set a new standard for excellence, transparency, and decentralization.
​What I am looking for:
I am building a professional, senior-level "Elite Team." I am looking for partners who are truly passionate about the vision—not just short-term gains. By combining our individual expertise and portfolios, we will establish Oferli’s collective professional reputation.
​Requirements:
​Proven Expertise: You must be a senior-level professional. Please provide your portfolio showcasing your best work in web and mobile development.
​Commitment: This is a founding partnership. We are looking for those who believe in the mission and are ready to tackle complex challenges together.
​Professionalism: We operate with high standards. Communication and efficiency are key.
​How We Work:
​Collaboration: We use professional, secure channels for all communications. Qualified candidates will be contacted via email to be invited to our private workspace on Notion to align on our roadmap and launch our upcoming projects.
​Decentralized Operations: We leverage Web3 tools for collaboration and compensation, maintaining a fully decentralized environment.
​Growth: We are launching with a core team of at least 5 founding partners, scaling to 10, to deliver high-impact results for our clients.
​Application Process:
If you are a senior professional ready to build a world-class, decentralized ecosystem, apply here on LaborX. Qualified candidates will be contacted via email for further professional vetting and onboarding.
​Let’s build the future, together.
​Sadr B
CEO, Oferli

 
 
we’re looking for a senior blockchain engineer to build low-latency execution infrastructure around hyperevm and hyperliquid-related trading systems.
 
this is not a frontend or dapp role. the focus is on real-time execution systems, chain-native infrastructure, and market-aware backend engineering where latency, ordering, and state correctness directly impact execution outcomes.
 
you will work on systems that operate under noisy, adversarial, and highly dynamic conditions, including delayed or missing websocket events, rpc inconsistencies, transaction lifecycle complexity, state desynchronization, retries, and recovery logic.
 
core responsibilities include building and maintaining realtime blockchain data pipelines, websocket and rpc streaming systems, execution orchestration layers, liquidity-aware routing logic, transaction lifecycle management, and integration with orderbook and market data systems.
 
we are specifically looking for engineers who think in systems rather than features. meaning understanding how data flows through pipelines, how state evolves over time, how failures propagate, and how to design systems that recover automatically without manual intervention.
 
areas of work include:
 
- realtime blockchain data ingestion
- mempool-aware execution flows
- transaction lifecycle handling
- execution sequencing and routing
- websocket and rpc infrastructure
- state synchronization systems
- liquidity and orderbook integration
- performance and latency optimization
 
you should be comfortable working with distributed systems, asynchronous event processing, and latency-sensitive backend architectures.
 
strong experience in one or more of the following areas is highly relevant:
 
- exchange infrastructure
- trading systems
- execution engines
- blockchain indexers
- realtime event systems
- arbitrage systems
- rpc/node infrastructure
- defi backend systems
- low-latency backend engineering
 
preferred technical stack:
 
- typescript / node.js
- go
- rust
- python
- postgres
- clickhouse
- redis
- kafka or similar messaging systems
- docker
- linux environments
- evm rpc internals
- websocket infrastructure
 
ecosystem familiarity:
 
- ethereum, arbitrum, base, optimism, bsc
- hyperliquid / hyperevm
- foundry
- ethers.js / viem
- geth / erigon / nethermind
- dex and amm mechanics
- liquidity math, slippage, gas strategy, routing logic
 
this role is not suitable for:
 
- frontend-only developers
- nft or basic dapp experience only
- tutorial-level web3 developers
- candidates without production systems experience
 
we value engineers who have built real systems where correctness, latency, and reliability matter under load. we care less about buzzwords and more about concrete systems you have personally built and operated.
 
ideal candidates can clearly explain:
 
- system architecture decisions
- bottlenecks and tradeoffs
- failure modes and recovery strategies
- latency considerations in real systems
- production debugging experience
 
working style:
 
- remote
- async-first
- low bureaucracy
- high ownership
- engineering-driven team
- direct technical communication
 
we strongly prefer practical engineering depth over polished presentation. if you have built or worked on systems involving realtime data, trading infrastructure, blockchain execution, or latency-sensitive backend systems, please include details of those systems when applying.
 

About the Role

As a Senior AI Analytics Engineer in our Data Team, you will serve as a key link between Data Engineering, Technology, and Product teams. Your primary responsibilities will involve operationalizing AI/LLM models, developing scalable data transformation pipelines, standardizing data models, and implementing best practices.

In addition to your core duties in analytics engineering, you will also be involved as a technical Business Analyst on certain data projects, collaborating with business units to translate operational needs into clear technical requirements.

Key Responsibilities

Data & AI Architecture: Develop and manage production-quality data models to connect raw data streams with downstream tools and BI, utilizing AI tools for data documentation, writing SQL/Python transformations, handling warehouse dialect conversions, and troubleshooting pipeline errors.

Analytics Engineering: Establish standardized data modeling approaches and build strong semantic layers to deliver clean, reliable data for analytics and reporting downstream.

Business & Requirements Analysis: Lead scoping discussions with various stakeholders to convert business requirements into functional specifications, user stories, and data mapping documents.

Business Logic Translation: Manage the alignment of data definitions across departments, a critical task that requires human intervention.

Data Quality & Governance: Implement automated testing, monitoring, and governance frameworks to ensure high reliability.

Performance Optimization: Enhance query performance, reduce warehouse costs, and streamline pipeline orchestration.

Requirements & Qualifications

Experience: Minimum of 5 years in Data Engineering, Analytics Engineering, or Data Science, with at least 2 years in an AI-focused environment.

Technical Mastery: Advanced skills in SQL, proficiency with modern data transformation and orchestration tools such as dbt, Airflow, Prefect, and Dagster, and deep knowledge of cloud data warehouses like Snowflake, Databricks, and BigQuery.

AI Technical Stack: Understanding of feature engineering, AI workflow lifecycles, and evaluation metrics, along with experience deploying AI workflows in production settings.

Business Analysis Skills: Ability to collect business requirements, define key metrics, and translate stakeholder needs into structured data assets as needed.

Software Engineering Principles: Strong background in version control using Git, CI/CD practices for data pipelines, and code testing for production environments.

We may utilize artificial intelligence tools for applicant screening, but final hires are based on human evaluation in conjunction with tool insights.

** About the Role**

We are seeking a talented individual as a Business & AI Process Automation Analyst to support our Corporate Development team in utilizing business data and operational processes to enhance decision-making, streamline execution, and drive measurable enhancements.

This role combines business and technology expertise and is ideal for candidates with a background in Computer Science, Information Systems, or related fields, who thrive on collaborating closely with business users. The successful candidate will collaborate with various departments including Corporate Development, Product, Operations, Finance, Engineering, Legal, Compliance, and other stakeholders.

Responsibilities

Cross-functional and External Stakeholder Delivery

Manage operational requirements, timelines, and issue resolution among different internal teams such as Corporate Development, Product, Operations, Finance, Engineering, Legal, and Compliance.

Oversee end-to-end operational workflows for new digital asset integrations and product offerings, from assessment to launch and ongoing maintenance.

Coordinate platform updates for critical asset events like token migrations, contract swaps, upgrades, rebrands, and asset deprecation.

Serve as the main operational point of contact for external project teams and important stakeholders.

Facilitate joint promotional campaigns, user engagement activities, and growth initiatives with external partners.

AI-Enabled Process Automation

Identify opportunities for applying AI, LLMs, Python, SQL, APIs, low-code tools, and workflow platforms to streamline repetitive analytical and operational tasks.

Design and implement multi-step workflows with data transformations, prompts, validation rules, operational procedures, and assigned business accountability.

Test and monitor workflows for accuracy, edge cases, failures, approval gates, and escalation procedures.

Business Analysis and Decision Support

Translate complex business inquiries into structured analyses, actionable recommendations, measurable metrics, and data requirements.

Analyze business performance, operational trends, product opportunities, bottlenecks, and process efficacy.

Develop dashboards, reports, and presentations to communicate findings and impact clearly.

Data Quality and Control

Investigate discrepancies across various reports, data sources, systems, and metric definitions to establish consistent business logic.

Document data sources, transformations, ownership, control requirements, and analytical assumptions.

Identify and escalate data quality, access control, privacy, security risks, and ensure AI-assisted outputs are validated before use.

Requirements

Minimum 3 years of professional experience in business intelligence, process automation, business analytics, or a related field.

A degree in Business Administration, Computer Science, Data Analytics, or a related discipline.

Proficiency in AI tools, workflow automation, low-code platforms, or agentic workflows for process improvement.

Strong business acumen and the ability to link analysis to priorities and measurable outcomes.

Excellent written and verbal communication skills to collaborate effectively across technical and business teams.

Structured, detail-oriented problem-solving approach with the ability to prioritize in ambiguous situations.

Must be based in Hong Kong and comfortable working with multiple functions and time zones.

Nice to Have

Experience with tools like Power BI, Tableau, Looker, Excel for building dashboards, reports, data pipelines, or analytical tools.

Proficiency in Python and SQL for data preparation, analysis, automation, or workflow development.

Experience in building or implementing AI agents, multi-step workflows with exception handling and human involvement.

Exposure to APIs, Git, n8n, Databricks, cloud data tools, or workflow orchestration platforms.

Background in financial services, fintech, digital assets, payments, trading, capital markets, or similar fast-paced technology environments.

We may utilize artificial intelligence tools for application assessments, but final hiring decisions are upheld by humans leveraging insights from the tools alongside other pertinent information. For further details on data processing, please contact us.

Job Overview

This part-time role requires working Friday to Sunday from 10:00 p.m. to 6:00 a.m. The Global Security Operations Center (GSOC) Agent plays a crucial role in supporting CleanSpark’s enterprise security operations by monitoring in real-time, detecting incidents, and coordinating responses across corporate and operational settings. Positioned at a 24/7 control center, this position involves maintaining awareness of situations, monitoring security technologies, coordinating responses, and ensuring prompt escalation of security events to safeguard CleanSpark’s personnel, assets, and activities.

To excel in this position, individuals must exhibit good judgment, meticulous attention to detail, effective communication skills, and the ability to stay updated on evolving security technologies and operational tools. This role operates on scheduled shifts within a 24/7 environment and involves participation in pre-shift and post-shift briefings to ensure operational consistency.

Key Responsibilities

Monitor various enterprise security systems such as CCTV, access control, alarm monitoring, drone platforms, Blue Force Tracking, OSINT resources, and related security technologies.

Detect, evaluate, prioritize, and escalate security incidents following established procedures and escalation guidelines.

Uphold enterprise-wide situational awareness by observing operational conditions, system alerts, and potential threats.

Act as the central communication hub during security incidents by liaising with on-site personnel, internal stakeholders, and emergency responders.

Dispatch and monitor security resources while documenting incidents and response actions within incident management systems.

Review videos, compile detailed documentation, and assist in security investigations when required.

Conduct regular system assessments and execute responsibilities in compliance with set Standard Operating Procedures (SOPs) and operational playbooks.

Engage in requisite training, maintain proficiency with GSOC technologies and security platforms, and contribute to continuous enhancement efforts.

Attend scheduled pre-shift and post-shift briefings to facilitate effective communication, operational preparedness, and smooth shift handovers.

This position demands professionalism, respect, effective communication, and collaborative teamwork within an inclusive environment.

Required Qualifications

High school diploma or equivalent; an associate’s or bachelor’s degree in related fields like Criminal Justice, Emergency Management, Homeland Security, is preferred.

1–3 years of experience in GSOC, SOC, dispatch, emergency communications, monitoring centers, military, law enforcement, or similar operational settings.

Proficiency in utilizing security technologies like CCTV, access control, alarm monitoring, or similar systems.

Capability to learn and proficiently operate multiple security platforms, monitoring systems, and operational technologies.

Strong analytical, organizational, and communication competencies.

Ability to maintain composure, apply sound judgment, and handle multiple priorities in a fast-paced environment.

Flexibility to work designated shifts, which may include nights, weekends, holidays, and overtime as necessary.

The compensation for this role is $26 - $28 per hour. The responsibilities may involve tasks that necessitate using a company vehicle or traveling between job sites. Candidates must meet the insurability criteria under CleanSpark's vehicle insurance policy.

CleanSpark upholds Equal Opportunity Employment principles. It offers equal employment opportunities, prohibits discrimination or harassment based on various characteristics, and aligns its policies with federal, state, and local laws governing employment terms and conditions.

The hiring process at CleanSpark may involve the use of Artificial Intelligence (AI) tools for tasks like application review, resume analysis, and response assessment. These AI tools support the recruitment process but do not supplant human judgment. Final hiring decisions are made by humans. For more information on the data processing procedures, applicants may reach out to CleanSpark for clarification.