G2i

Role Description G2i is partnering with Human Cloud, a technology-enabled platform that helps organizations discover, evaluate, and deploy flexible workforce solutions. We’re looking for a hands-on Data Analytics & Visualization Engineer to help build and enhance enterprise analytics and data visualization solutions. This role is ideal for a mid-to-senior-level engineer who combines strong execution skills with the ability to translate business requirements into clear, reliable, and useful data products. You’ll work across analytics, visualization, and application development using Python, TypeScript, and enterprise productivity ecosystems. You should also be comfortable incorporating AI tools into your everyday development and analytical workflows. What You’ll Do - Design and build enterprise-grade analytics and data visualization solutions - Develop interactive dashboards, reporting experiences, and data-driven applications - Use Python to transform, analyze, and prepare data for reporting and visualization - Build frontend features and visualization components using TypeScript - Integrate analytics solutions with enterprise Microsoft tools and Google Workspace - Translate business questions and stakeholder needs into practical technical solutions - Improve the usability, performance, and maintainability of existing analytics platforms - Use AI-assisted tools to accelerate development, analysis, documentation, and problem-solving - Collaborate with technical and non-technical stakeholders in a remote environment - Take ownership of deliverables from initial requirements through implementation Qualifications - Professional experience building analytics platforms, dashboards, or data visualization products - Strong proficiency with Python for data processing, analysis, or backend development - Experience with TypeScript and modern web application development - Practical knowledge of data visualization principles and libraries or BI platforms - Experience working with enterprise data sources, APIs, and reporting workflows - Familiarity with the Microsoft enterprise ecosystem, such as Power BI, Excel, Azure, Microsoft 365, or related tools - Familiarity with Google Workspace and its data or productivity tools - Experience using AI coding assistants or generative AI tools in day-to-day workflows - Ability to work independently, make sound implementation decisions, and deliver production-ready solutions - Strong written and verbal English communication skills - Availability to collaborate with teams working primarily across North American time zones Nice to Have - Experience with Power BI, Tableau, Looker, D3.js, Plotly, Recharts, or similar technologies - Experience building custom analytics applications rather than working exclusively in traditional BI tools - Knowledge of SQL, data modeling, ETL/ELT workflows, and cloud data platforms - Experience integrating Microsoft and Google Workspace services through APIs - Previous experience in consulting, client-facing delivery, or fast-moving project environments - Experience using LLMs or AI agents to support analytics, reporting, or data exploration What Success Looks Like You can quickly understand business needs, work effectively within an existing enterprise technology environment, and turn complex data into intuitive, actionable experiences. You are comfortable owning execution, collaborating remotely, and using modern AI-enabled workflows to deliver high-quality work efficiently.

Role Description We're seeking a Mid/Senior Data Analytics & Visualization Engineer who thrives at the intersection of engineering, analytics, and product. You'll help design and build internal analytics and visualization experiences that empower teams to explore data, monitor business performance, and make better decisions. This is a hands-on engineering role focused on execution—you'll spend most of your time building rather than managing. We're looking for someone comfortable working in a fast-moving environment who already uses AI tools as part of their daily development workflow. What You'll Do - Build scalable analytics applications and interactive data visualization experiences. - Develop backend services and data processing pipelines using Python. - Build modern frontend interfaces using TypeScript. - Transform complex business data into intuitive dashboards and visualizations. - Collaborate with product, design, and business stakeholders to define analytics requirements. - Improve data quality, performance, and usability across analytics platforms. - Leverage AI-assisted development tools to accelerate delivery and improve engineering efficiency. Qualifications - Professional experience building production software with Python. - Strong experience with TypeScript. - Experience building enterprise analytics platforms, BI applications, or data products. - Strong understanding of data modeling and analytics workflows. - Experience building interactive data visualizations. - Comfortable working across frontend and backend components. - Experience consuming APIs and working with structured datasets. - Strong communication skills in English. - Comfortable working independently in a remote environment. - Regular use of AI coding tools (such as ChatGPT, Claude, Cursor, GitHub Copilot, or similar) as part of your daily workflow. Requirements - Experience with modern visualization libraries (D3.js, Observable, Vega, Plotly, Recharts, ECharts, etc.). - Experience with SQL and analytical databases. - Experience building internal tooling or business intelligence platforms. - Cloud experience (AWS, GCP, or Azure). Interview Process - Resume review - Client review call - 1–2 technical/client interviews - Offer Benefits - Contract (3–6 months, with possibility of extension or full-time conversion). - Budgeted around USD $60K for the initial engagement (open based on scope and experience).

• Design, develop, and maintain scalable full-stack applications using React.js, Node.js, and TypeScript. • Integrate LLMs and AI services into production features — structured outputs, retrieval-augmented generation (RAG), and agentic or tool-using workflows. • Build and maintain the supporting data and retrieval layers for AI features (embeddings, vector search, context pipelines). • Measure and improve AI feature quality, reliability, latency, and cost through evaluation and guardrails. • Collaborate with cross-functional teams to define, design, and ship new features. • Implement best practices for platform engineering, performance optimization, and security. • Work closely with DevOps to automate and streamline deployment processes. • Write clean, testable, and efficient code, and participate in code reviews. • Stay current with emerging AI and web technologies and share knowledge with peers.

Role Description Our client is building next-generation financial infrastructure that enables real-time movement of digital money across traditional banking systems and digital asset networks. They are looking for a technically strong Client Support Engineer to serve as the primary support contact for partner financial institutions, helping diagnose, troubleshoot, and resolve operational and technical issues across their payments platform. This role sits at the intersection of technical support, operations, and engineering, making it ideal for candidates who enjoy solving complex problems, working directly with customers, and improving support processes in fast-paced environments. What You'll Do - Serve as the Primary Technical Contact for Financial Institution Partners - Act as the first point of contact for partner banks and financial institutions experiencing technical or operational issues. - Investigate and resolve support requests related to API behavior, connectivity, payment processing, and operational workflows. - Communicate effectively with both technical and non-technical stakeholders throughout the resolution process. - Manage and Resolve Operational Exceptions - Monitor support queues and exception management systems. - Triage, investigate, and drive incidents to resolution. - Escalate complex issues to Engineering when necessary and coordinate follow-through until closure. - Conduct root cause analysis and document findings. - Improve Support Operations - Create and maintain support documentation, runbooks, troubleshooting guides, and escalation procedures. - Identify recurring issues and work with Engineering and Product teams to improve reliability and reduce support volume. - Contribute to the design and scaling of support processes, monitoring practices, and operational workflows. - Collaborate Cross-Functionally - Partner closely with Engineering, Product, and Operations teams. - Provide actionable feedback based on customer and operational trends. - Help shape a scalable support function within a growing fintech environment. Qualifications - 3+ years of experience in a client-facing Support Engineering, Technical Support Engineering, Solutions Engineering, or Production Support role. - Experience supporting customers in fintech, payments, banking, financial infrastructure, or related industries. - Strong troubleshooting and root cause analysis skills. - Experience working directly with APIs, including testing and debugging REST APIs using tools such as Postman. - Familiarity with monitoring and observability platforms such as Grafana, Datadog, Splunk, or similar. - Working knowledge of Linux command line and networking fundamentals. - Excellent written and verbal communication skills. - Ability to manage multiple support cases independently and drive issues to resolution. Nice-to-Have Qualifications - Experience supporting banks, payment processors, or financial institutions. - Knowledge of payment systems, money movement, banking infrastructure, or financial operations. - Experience with blockchain technology, digital assets, stablecoins, tokenized deposits, or cryptocurrency platforms. - Familiarity with automation and configuration management tools such as Ansible, Chef, or Terraform. - Experience working in startup or high-growth environments. What Success Looks Like - Support tickets are resolved accurately and efficiently. - Partner institutions receive timely and professional technical support. - Operational incidents are investigated thoroughly and documented clearly. - Support processes become increasingly scalable through automation, documentation, and continuous improvement. - Strong collaboration exists between Support, Engineering, and Product teams to improve platform reliability and customer experience. Benefits - Competitive salary - USD 88-100K (up to 110k for NY/SF area). - Equity participation. - Comprehensive medical, dental, and vision coverage. - 401(k) with employer matching. - Flexible PTO. - Fully remote work environment. Location Requirement - Candidates must be based in the United States and willing to travel occasionally as needed.

• You'll own product areas end-to-end — architecture, implementation, and iteration — across our agent platform. • That means building and maintaining core application infrastructure in React, Next.js, TypeScript, Node, and PostgreSQL. • Designing the AI layer that makes our agents actually work: multi-model orchestration, RAG pipelines and vector databases, semantic memory, prompt caching strategies, and token usage tracking. • Build and maintain eval and testing harnesses to keep agent behavior reliable as models and prompts evolve. • Work closely with the founding team to translate fuzzy product ideas into shipped, working systems.

• Own backend systems and infrastructure end-to-end, from design through deployment and scaling • Build performant, reliable APIs and services that power core financial products • Design and implement scalable architectures on AWS using Node (TypeScript) • Make pragmatic tradeoffs between speed, reliability, scalability, and maintainability • Ship production code frequently while maintaining high quality standards • Help establish technical patterns and best practices for the engineering team • Interface effectively with product engineers and other stakeholders

• Take full ownership of complex, escalated, or high-risk accounts — from first risk signal through to resolution. • Diagnose root cause behind every at-risk engagement: strategy, execution, expectation misalignment, or delivery failure — and build the right intervention. • Lead high-stakes conversations at founder and C-suite level — resetting expectations, rebuilding trust, and redirecting momentum toward outcomes. • Monitor engagement-health signals across your accounts and intervene before issues become formal escalations. • Build targeted recovery plans that address root causes — not surface complaints — and execute them at pace. • Report weekly on case outcomes, revenue protected, churn signals, and patterns needing broader attention. • Lead live advisory sessions with founders — implementation-focused guidance across offer, outbound, pipeline, and execution. • Translate client reality into structured, actionable feedback for internal delivery teams. • Contribute to escalation frameworks, retention playbooks, and client-risk systems that work beyond your own caseload.

Role Description We seek a talented and motivated Senior Front-End Web Developer to join our dynamic team. The ideal candidate will have a strong foundation in React, JavaScript, and TypeScript and a passion for creating visually appealing and highly functional web applications. This role will involve collaborating with cross-functional teams to design, develop, and implement front-end solutions for our diverse range of projects. The candidate must be based in a GMT+4 to GMT+9 time zone. Key Responsibilities - Develop and maintain web applications using React, JavaScript, and TypeScript. - Translate designs and wireframes into high-quality code. - Optimise applications for maximum speed and scalability. - Ensure the technical feasibility of UI/UX designs. - Collaborate with back-end developers and other team members to establish objectives and design more functional, cohesive codes to enhance user experience. - Implement performant code to ensure the product works across devices of various capacities. - Write clean, scalable, and documented code with an emphasis on maintainability. - Debug and troubleshoot layout and scripting issues across a variety of browsers. - Participate in code reviews and contribute to team knowledge sharing. Required Skills - Strong experience with React and Typescript. - Experience with any modern state management library (Finite State Machine libraries preferred - e.g XState). - Strong experience with single-page applications (SPA) and state management. - Experience with a CSS-in-JS framework for styling. - Knowledge of front-end build pipelines and tools. - Understanding of general linear algebra and its application in graphics and animations. - Experience with GraphQL APIs and asynchronous request handling. - Strong problem-solving skills and attention to detail. - Experience with maintaining or deploying libraries or plugins is nice to have. - Frontend testing experience is required. Qualifications - Bachelor's degree in Computer Science or a related field or equivalent experience. - 4+ years of professional experience in front-end web development. - Demonstrable experience with React, JavaScript, and TypeScript. Nice to Have - Experience working with canvas-based environments. - Familiarity with cloud services and infrastructure. - Experience with Rust is nice to have. - Proficient in AI-native workflows to accelerate development while ensuring AI-generated code meets high standards for performance, security, and accessibility.

Role Description This role is ideal for someone who enjoys solving real-world industrial data challenges. You'll work directly with data generated from mining operations, integrating historian systems, sensor data, and operational datasets into cloud-native platforms that support advanced analytics and machine learning. The work goes beyond traditional ETL. You'll help build the data backbone that enables optimization models and operational recommendations to flow back into industrial systems used by mine operators. - Design and maintain data pipelines that ingest industrial and historian data into GCP. - Process and transform large-scale Parquet datasets generated from mining operations. - Load and optimize data within BigQuery and Bigtable environments. - Build reliable data integration workflows between operational technology (OT) systems and cloud infrastructure. - Support machine learning teams by providing clean, accessible, production-ready datasets. - Help operationalize recommendations generated by analytics and ML systems back into historian or control environments. - Collaborate closely with Data Scientists, Engineers, and mining domain experts. - Troubleshoot data quality, reliability, and performance issues across the data platform. Qualifications - 5+ years of experience in Data Engineering or Data Platform Engineering. - Strong experience with Google Cloud Platform (GCP). - Hands-on experience with: - BigQuery - Bigtable - Parquet - Docker - Experience building and maintaining production-grade ETL/ELT pipelines. - Strong SQL skills and experience working with large-scale datasets. - Experience integrating data from multiple operational systems. - Ability to work independently in a remote environment. Requirements - Experience in Mining, Metals, Energy, Manufacturing, Industrial IoT, or Process Industries. - Experience working with: - Industrial historians (OSIsoft PI, AVEVA Historian, Canary, etc.) - SCADA systems - Process control systems - Time-series industrial data - Experience supporting ML or AI-driven products. - Familiarity with industrial operations and production optimization workflows. - Spanish proficiency is a plus. Benefits - Direct impact on real-world mining operations. - Work at the intersection of industrial systems, cloud infrastructure, and AI. - Collaborate with a highly specialized team focused on operational optimization. - Opportunity to solve complex data integration challenges rarely seen in traditional SaaS environments. - Fast hiring process with direct access to technical and executive leadership. Interview Process - G2i Recorded Interview - Professional background review - Targeted technical deep dive - Client Interview - Conversation with the VP of Data Science - Decision - Fast turnaround after final interview Location Remote across South America. Candidates with mining industry experience from Chile, Peru, Brazil, Argentina, or other mining-focused regions are especially encouraged to apply.

Role Description We're looking for a Data Scientist with strong machine learning expertise and practical mining industry experience to help build and improve predictive models used across mining and mineral processing operations. This is not a "train once and deploy" environment. You'll develop and maintain models that continuously adapt to changing geological conditions, ore variability, and operational differences across multiple mine sites. You'll work closely with domain experts and engineering teams to deliver measurable improvements in plant performance, recovery, and production outcomes. Mining operations often require ongoing model monitoring and adaptation because ore characteristics and process conditions evolve over time. What You'll Do - Build, deploy, and improve machine learning models for mine-to-mill optimization - Analyze large-scale mining and processing datasets to identify operational improvement opportunities - Develop predictive models related to ore characteristics, fragmentation, recovery, flotation, throughput, and plant performance - Monitor model performance and address model drift across sites and changing geological conditions - Partner with mining engineers, metallurgists, and operations teams to translate business challenges into ML solutions - Work with structured and unstructured industrial datasets to support production decision-making - Design experiments and evaluate model performance in real operational environments - Contribute to MLOps and model monitoring practices for production systems Qualifications - 5+ years of experience in Data Science, Machine Learning, or Applied AI - Strong Python and machine learning fundamentals - Experience building production ML systems and maintaining models over time - Hands-on experience with: - Google Cloud Platform (GCP) - BigQuery - Parquet-based data pipelines - Model monitoring and performance tracking - Strong statistical modeling and experimentation skills - Experience working with large operational or industrial datasets - Excellent communication skills and ability to collaborate with cross-functional teams Requirements - Direct experience in mining, mineral processing, metallurgy, or mine-to-mill optimization - Understanding of: - Ore variability - Rock hardness and fragmentation - Flotation processes - Recovery optimization - Mill performance drivers - Production process analytics - Experience supporting multiple operational sites with varying geological conditions - Experience with time-series modeling and industrial process optimization Nice to Have - Experience with MLOps frameworks - Knowledge of process control systems and industrial data platforms - Experience with predictive maintenance or optimization systems - Background in copper, gold, or base metals operations Benefits - Competitive compensation (~USD $140,000/year, depending on experience) - Fully remote - Opportunity to work on cutting-edge AI applications in the mining industry - Small, highly technical team with direct impact on product and customer outcomes - Fast-moving hiring process Interview Process - G2i recorded interview (experience review + targeted technical deep dive) - Client interview with VP of Data Science - Final decision