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PredictHQ logo

Senior Software Engineer

PredictHQ
Posted Jul 2, 2026, 7:51 AM UTC
🇳🇿New Zealand🏢Hybrid📁Engineering & Development
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Senior Software Engineer Own the backend systems that turn messy, real-world event data into the trustworthy insight our customers build decisions on About PredictHQ AI and forecasting systems have a blind spot: the real-world conditions that shift demand land as surprises instead of signals. PredictHQ closes that gap. PredictHQ is the real-world context platform powering enterprise AI decisions, trusted by the world's largest enterprises, including Uber, Domino's and Accor. We explain more than 60 per cent of real-world demand variability, grounding models in verified spatial, temporal and economic reality so businesses can make high-stakes decisions on pricing, staffing and inventory with confidence. With Beam, our relevancy engine, Bolt, our rapid integration framework, and native MCP support for AI agent workflows, we're defining a new category at the intersection of AI, data and enterprise decision-making. We're a company in motion, backed by strong fundamentals and hard technical problems. Founded in 2016 and backed by Lightspeed Venture Partners, Sutter Hill Ventures, and Aspect Ventures, PredictHQ has offices in Auckland and San Francisco. Job Purpose We're looking for a Senior Software Engineer to join our Sustained Engineering team: a high-leverage group responsible for the backend systems that ingest, process, and enrich event data at the core of our platform - data that directly powers the decisions our customers make. In this role, you'll own the backend pipeline services that turn raw, messy real-world signals into trustworthy, structured insight. You'll improve and evolve the APIs and ingestion paths that scale with our data, and you'll have real input into how we source and model events as the platform grows. You’ll thrive in this role if you enjoy solving the hard problems that come with operating at scale: throughput, data quality, and system resilience under real production load. You'll work hands-on across a modern Python stack (FastAPI, Kafka, Elasticsearch), with a strong observability and reliability culture - using agentic workflows alongside monitoring and alerting to catch and resolve issues before they ever reach a customer. You'll work closely with product and data specialists, pragmatically identifying where the system can be better and driving those improvements yourself. As a senior engineer, you'll help set the technical bar for the team - championing best practices, mentoring other engineers, and shaping a culture of curiosity as our platform and data scale. 🔑 Key Responsibilities Build, improve and maintain scalable APIs, data pipelines, and services using Python, FastAPI, Kafka, Elasticsearch and others. Own and improve monitoring and alerting for our pipeline services, ensuring fast detection and resolution of production issues during monitoring rotations. Work within and contribute to evolving our architecture, standards, and engineering practices. Collaborate with cross-functional teams - including product managers, data specialists, and fellow engineers - to deliver impactful solutions. Proactively identify and address technical debt, performance bottlenecks, and system reliability issues. Conduct thoughtful code reviews and share knowledge to raise the technical bar. Mentor and support other engineers through pairing, feedback, and guidance. Help shape and uphold a strong engineering culture with pragmatic best practices (CI/CD, observability, testing, agentic workflows etc.) Stay current with modern tools, techniques, and AI trends - and apply them meaningfully. ⭐ Skills, Knowledge and Competencies Strong experience building production systems in Python. Proficient with FastAPI or similar modern API frameworks. Comfortable with distributed systems and event-driven architecture (Kafka). Familiarity with search technologies like Elasticsearch. Comfortable working with Kubernetes, including writing and maintaining Helm charts. Solid understanding of CI/CD, Docker, and cloud-native infrastructure (AWS). Writes clean, testable, maintainable code with a strong focus on quality and performance. Diagnoses and resolves technical issues across the stack independently. Communicates clearly and collaborates effectively across teams. Proactively mentors and supports other engineers. Takes initiative and ownership of technical outcomes. Curious, pragmatic, and continuously learning - especially around AI and data-driven tech. Bonus: experience with ML pipelines or open source contributions. 🤝 General Applicants for this position must have New Zealand residency or a valid New Zealand work visa. Carry out all work in line with PredictHQ's policies, relevant legislation, and applicable industry standards. Based in Auckland, this role follows our hybrid approach, combining the flexibility of working from home with at least two days a week in the office to foster team connection and collaboration. ✨ Benefits Health Insurance administered by Unimed Paid Birthday Leave and Paid Family and Friends Day Leave Strong focus on your training and development 10 weeks of fully paid parental leave Flexible work arrangements A hybrid work environment centred on collaboration, agility and fun Options in a fast-growing company in its early stages $500 annual stipend to support your work-from-home setup 💛 Our Values PredictHQ is about teamwork to achieve huge things. We are building innovative and complex products, so our empathetic, hard-working culture is key to our success. We are proactive in helping our teammates grow and thrive in their careers, as well as making sure everyone can put their family and friends first. Department Research & Development Locations Auckland Remote status Hybrid About PredictHQ PredictHQ is the real-world context platform that improves model performance and AI inference at decision time. By harnessing global events and learning from trillions in demand data, we explain and predict demand variability so enterprises can make accurate, trusted decisions. Founded in 2016 Co-workers 50

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