This is a remote position. DAYSHIFT, REMOTE (INDIA-BASED) IT & AI INTEGRATION DEVELOPER Client : High Voltage Electrical Contractors Headquarters : Sydney NSW Department : Technology & Innovation |Reports To Managing Director Salary Range : $12AUD per hour (negotiable) Remote work (India based) Full-Time 40 hours Start Date Immediate / By Arrangement The client is one of Sydney's fastest-growing high-voltage electrical contracting businesses. Operating since 2021 and now exceeding $15M in annual revenue, we hold Level 1 ASP accreditation with both Ausgrid and Endeavour Energy, and deliver complex HV infrastructure projects across data centres, utilities, commercial and industrial sectors. With 40+ staff including 26 field technicians, we operate as a principal GEC with in-house HV capability as our core differentiator. We are investing heavily in technology and automation to scale our operations, improve project delivery efficiency, and lead the industry in digital-first field operations. This is a greenfield opportunity for someone who wants to build real systems that make a real difference. THE OPPORTUNITY We are seeking a talented IT & AI Integration Developer to lead the development and implementation of technology solutions across the Nebula group. This is a newly created, high-impact role reporting directly to the Managing Director. You will own the digital transformation roadmap for the business — from automating field reporting and job management workflows, to deploying AI-powered tools that reduce administrative overhead and enhance decision-making at every level. This is not a support desk role. We are looking for a builder — someone who can design, develop, and deploy production-ready solutions in a dynamic, fast-paced electrical contracting environment. KEY RESPONSIBILITIES AI Integration & Automation • Design and deploy AI-powered tools and workflows to automate administrative, operational and reporting tasks • Integrate large language model (LLM) APIs (e.g. OpenAI, Anthropic Claude) into internal business systems • Develop intelligent document processing solutions for quotes, variations, compliance forms and timesheets • Build and maintain AI-assisted reporting, cost tracking and project management dashboards Software & Systems Development • Develop web-based and mobile-compatible internal applications (field reporting apps, job management tools, EOD systems) • Build custom integrations between Xero, CRM, project management and field operations platforms • Maintain and extend existing platforms including the Nebula website (Wix/custom) and internal portals • Own the full software development lifecycle from requirements gathering through to deployment and support Data & Analytics • Design and maintain data pipelines for operational KPIs, financial performance and project tracking • Build automated dashboards for leadership across business units (Service, Projects, Commissioning) • Support the Finance Manager and Operations Director with data-driven reporting infrastructure IT Infrastructure & Security • Manage company IT assets, device naming/tracking and user access systems • Ensure cybersecurity best practices across all platforms and integrations • Support onboarding and offboarding processes from a systems and access perspective Requirements SKILLS & EXPERIENCE — REQUIRED • 3+ years of software development experience with a demonstrable portfolio of shipped products • Strong proficiency in at least one modern backend language (Python, Node.js, or similar) • Hands-on experience integrating AI/LLM APIs into production systems (OpenAI, Anthropic, Gemini, or similar) • Experience building web applications, REST APIs and internal tooling • Proficiency with databases (SQL and/or NoSQL) and data pipeline fundamentals • Strong problem-solving skills — ability to work through ambiguous requirements and deliver pragmatic solutions • Excellent communication skills with the ability to translate technical concepts for non-technical stakeholders SKILLS & EXPERIENCE — HIGHLY REGARDED • Experience in a trades, construction, facilities or field-services business environment • Familiarity with no-code/low-code platforms (e.g. Make, Zapier, Base44, Bubble) alongside custom development • Experience integrating with Xero, MYOB, or other accounting platforms • Knowledge of workflow automation and BPM tooling • Mobile app development experience (React Native, Flutter or similar) • Exposure to prompt engineering, fine-tuning, RAG pipelines or custom AI agent development • Relevant tertiary qualifications in Computer Science, Software Engineering, or a related field Benefits WHAT WE OFFER • Direct access to and collaboration with the Managing Director — your work will matter from day one • Greenfield mandate — you will shape the technology stack and digital strategy from the ground up • Competitive salary package commensurate with your experience and the impact of the role • A genuinely dynamic and ambitious team culture — we move fast, we back our people, and we invest in growth • Opportunity for career growth as the business scales toward a multi-state operation • Modern workplace at our Wetherill Park operations hub • Exposure to complex, high-value infrastructure projects that are shaping Sydney's energy future OUR CULTURE We believe in leaders at every level. We are not a business where you wait to be told what to do — we hire people who take ownership, think commercially, and bring solutions. We have built a high-performance culture built on accountability, respect and the drive to deliver exceptional outcomes for our clients. If you are the type of person who gets energy from solving complex problems, who takes pride in work that actually ships and makes a difference, and who wants to be part of a company that is genuinely growing — we want to hear from you. HOW TO APPLY To apply, please submit your CV and a brief cover letter outlining your most relevant AI integration or automation project — what you built, what problem it solved, and what the outcome was. We are reviewing applications on a rolling basis and encourage early submissions.

Job Title: Full-Stack AI Engineer Position Type: Full-Time, Remote Working Hours: U.S. client business hours (with flexibility for model deployments, experimentation cycles, and sprint schedules) About the Role: Our client is seeking a Full-Stack AI Engineer to design, build, and deploy AI-powered applications. This role requires bridging software engineering with applied machine learning, ensuring that models are integrated into production systems that are scalable, reliable, and user-friendly. The Full-Stack AI Engineer combines back-end services, front-end interfaces, and machine learning pipelines to deliver practical, business-driven AI solutions. Responsibilities: AI Model Integration: - Deploy pre-trained and fine-tuned ML/LLM models (OpenAI, Hugging Face, TensorFlow, PyTorch). - Wrap models in APIs (FastAPI, Flask, Node.js) for scalable inference. - Implement vector search integrations (Pinecone, Weaviate, FAISS) for retrieval-augmented generation (RAG). Data Engineering & Pipelines: - Build ETL pipelines for ingesting, cleaning, and transforming text, image, or structured data. - Automate data labeling, preprocessing, and versioning with Airflow, Prefect, or Dagster. - Store and manage datasets in cloud warehouses (Snowflake, BigQuery, Redshift). Application Development (Full-Stack): - Build front-end UIs in React, Next.js, or Vue to surface AI-powered features (chatbots, dashboards, analytics). - Design back-end services and microservices to connect models to business logic. - Ensure responsive, intuitive, and secure interfaces for end users. Infrastructure & Deployment: - Containerize ML services with Docker and deploy to Kubernetes clusters. - Automate CI/CD pipelines for model updates and application releases. - Monitor latency, cost, and model drift with MLflow, Weights & Biases, or custom dashboards. Security & Compliance: - Ensure AI systems comply with data privacy standards (GDPR, HIPAA, SOC 2). - Implement rate limiting, access control, and secure API endpoints. Collaboration & Iteration: - Work with data scientists to productionize prototypes. - Partner with product teams to scope AI features aligned with business needs. - Document systems for reproducibility and knowledge transfer. What Makes You a Perfect Fit: - Strong coder with a foundation in both full-stack development and applied ML/AI. - Comfortable building prototypes and scaling them to production-grade systems. - Analytical problem solver who balances performance, cost, and usability. - Curious and adaptable, staying current with emerging AI/LLM tools and frameworks. Required Experience & Skills (Minimum): - 3+ years in software engineering with exposure to AI/ML. - Proficiency in Python (PyTorch, TensorFlow) and JavaScript/TypeScript (React, Node.js). - Experience deploying ML models into production systems. - Strong SQL and experience with cloud data warehouses. Ideal Experience & Skills: - Built and scaled AI-powered SaaS products. - Experience with LLM fine-tuning, embeddings, and RAG pipelines. - Knowledge of MLOps practices (Kubeflow, MLflow, Vertex AI, SageMaker). - Familiarity with microservices, serverless architectures, and cost-optimized inference. What Does a Typical Day Look Like? A Full-Stack AI Engineer’s day revolves around connecting models to real-world applications. You will: - Review and refine model APIs, testing latency and accuracy. - Write front-end code to surface AI features in user-friendly interfaces. - Maintain pipelines that clean and prepare new datasets for training or fine-tuning. - Deploy updates through CI/CD pipelines, monitoring cost and performance post-release. - Collaborate with product and data science teams to prioritize AI features that solve real user problems. - Document workflows and results so solutions are repeatable and scalable. In essence: you ensure AI moves from prototype to production — reliable, compliant, and impactful. Key Metrics for Success (KPIs): - Successful deployment of AI features to production on schedule. - Application uptime ≥ 99.9% and inference latency < 500ms for key endpoints. - Reduction in manual workflows replaced by AI features. - Model performance tracked and stable (accuracy, drift, false positives/negatives). - Positive user adoption and satisfaction of AI-driven features. Interview Process: - Initial Phone Screen - Video Interview with Pavago Recruiter - Technical Assessment (e.g., deploy a small ML model with API endpoints and basic front-end integration) - Client Interview(s) with Engineering Team - Offer & Background Verification

• Design scalable AI architectures for customer use cases in line with enterprise and security standards • Lead implementation of AI software components such as model serving, orchestration, retrieval, and integrations • Run time-bound proofs of value to demonstrate business outcomes quickly and clearly • Help migrate AI workloads between cloud, on-premises, and hybrid environments on Dell infrastructure • Enable customer engineers and platform teams to support and extend solutions after handover • Design, configure, and implement AI solution stacks, including model serving, orchestration, retrieval pipelines, vector stores, and related components • Select practical tools and patterns to avoid tooling sprawl and deliver working prototypes and PoVs tied to clear success measures • Lead PoV sprints (typically a few weeks): refine scope, build and iterate on solutions, and present outcomes and recommendations to stakeholders • Plan and execute cloud-to-on-prem and hybrid migration patterns for AI workloads onto Dell infrastructure, optimizing performance, reliability, and security • Take shared responsibility for production readiness and early production stability, including monitoring, performance optimization, and issue triage • Work closely with AI Data Specialists to define and consume AI-ready data pipelines that support performance and reliability • Collaborate with AI Strategists and Enterprise Architects to align technical scope with business outcomes and target-state architectures • Provide documentation, runbooks, and knowledge transfer to customer teams, and contribute to Dell AI Factory reference architectures and playbooks • Mentor other technical team members on AI architecture patterns, Dell AI infrastructure capabilities, and responsible AI practices

• Design end-to-end AI systems: combining LLMs, embeddings, retrieval pipelines, and structured outputs into reliable product features. • Build grounding and retrieval layers: indexing docs, OpenAPI specs, and customer data to support accurate, context-aware generation. • Define evaluation systems: measuring accuracy, latency, cost, and user impact; building feedback loops to continuously improve quality. • Handle real-world complexity: malformed specs, inconsistent docs, edge-case APIs, and ambiguous user queries. • Make architectural tradeoffs: latency vs. quality, cost vs. coverage, deterministic vs. generative approaches. • Own production reliability: observability, fallbacks, rate limiting, and safe degradation when systems fail. • Work across the stack: from model orchestration and backend systems to the UI surfaces that expose them.