GRIDSIGHT

Role Description We're hiring our first full-time product designer: a senior IC who will shape how utilities see and operate their networks. This is not a typical SaaS product design role. In most SaaS, the interface is the essence of the product, so a designer can reason about the whole thing through what's on screen. At Gridsight, the core of the product lives underneath: pipelines of time-series data, transformations, and the concepts that turn billions of raw meter readings into meaning. This role demands reasoning from the data outward, treating the interface as an expression of that system rather than its definition. - The unit of design here is the reusable primitive, not the screen. - Our customers rarely need an answer designed; what needs designing is the capability that produces answers. - The right building blocks solve today's problem but also the next ten variations of it. - Quality comes from economy rather than polish: the right symbols, primitives, and conventions exposing more of the product through less surface area. - You'll own the visual language of how a utility reads its own grid: how a feeder, a fault, or a load profile renders as something a power engineer can interpret at a glance. - You'll embed with our product squads day to day, and you'll be the strongest voice for the experience dimension in a product org where the best solutions are co-developed across experience, data, and technology. - This is a senior role by necessity: the ambiguity is too high for someone who needs direction. - It's a role with room to grow in many directions including building and leading the design function. - AI-assisted work is the norm at Gridsight, not the exception, and design is no different. - We're looking for someone already using AI to amplify their discovery, exploration, and output and who is energized by how fast that frontier is moving. Qualifications - Systems thinking and conceptual modelling as your core skill. - The ability to translate complexity into simplicity. - Comfort reasoning below the interface. - Your best work at low fidelity. - Discovery as a default. - Enough seniority for ambiguity. - Product-first thinking. - You may currently be titled a product designer, a UX architect, an information architect, a design engineer, a product manager on data products, or even a data scientist with a design practice. - The fast track is founding designer experience in a scaled product company, otherwise we expect you have a few laps under your belt. Requirements - Experience with data products, developer/API products, or enterprise B2B. - Experience in technical domains: energy, infrastructure, geospatial, or scientific tooling. - A formal education that trained abstraction: design theory and HCI, or mathematics, computer science, engineering or economics. - Experience as a founding or sole designer in a product company. Benefits - Competitive salary and equity package. - Remote-first, with head office in Sydney. - A talented team of engineers, data scientists, and power systems specialists working on hard problems that matter. - The chance to define design at Gridsight from the ground up.

Role Description You will design and develop software and data science products that provide electricity utilities key insights into the state and operation of their grids. Your work will help to build up the picture of how grids can be managed more efficiently and dynamically, paving the way for the connection of more renewables, sooner. - Design, build, and maintain software products and data science models capable of detecting, characterising or predicting key components, properties and events of electricity grids. - Obtain data from disparate sources to inform and support modelling, by performing data discovery and/or developing automated retrieval pipelines as needed. - Ensure software and model capabilities, coverage and performance align with customer requirements, directly engaging with customers from time to time in order to do so. - Collaborate with Software Engineers, Data Engineers, and other Product teams to understand data science requirements and translate them into technical solutions. - Establish and follow data, scientific, MLOps and software engineering best practices including testing, validation, documentation, monitoring, version control and code reviews. - Contribute to data science strategy and architectural decisions. Qualifications - 3+ years in data science roles with demonstrable impact. PhD not required, but completion of a doctorate with a relevant focus on data science – especially Bayesian methods – may be counted towards this requirement. - Proficiency in Python or similar language, architecture, system design, version control, testing practices, code review, CI/CD. - Mathematical modelling, numerical methods, applied statistics. - Experience developing, training, testing and validating machine learning models, as well as deploying them to production. Requirements - Experience with Bayesian methods (parameter estimation, hierarchical modelling, sampling, etc). - Experience with Monte Carlo methods. - Experience in energy, utilities, or IoT/sensor data domains. - Experience building data products for customer consumption. - Experience delivering software/data products to customers, and iterating based on their feedback. - Experience discovering and integrating diverse data sources into complex modelling pipelines, both ML and otherwise. - Experience designing and implementing agentic workflows. - Experience optimising Python workflows, e.g. via parallel/distributed solutions or development of interfaces to optimised lower-level libraries. - Experience working in remote or distributed teams. - Data governance or compliance experience in regulated industries. Benefits - Competitive salary and equity package. - Remote-first, with head office in Sydney. - A talented team of engineers, data scientists, and power systems specialists working on hard problems that matter. - A role with clear growth pathways into product and tooling, or deeper customer ownership.

Role Description We're hiring a Senior or Staff-level Data Scientist to help design and build the powerflow and optimisation engines at the core of our platform. This role sits at the heart of our work on calculating safe, real-time capacity for distributed energy resources within network constraints and turning those calculations into forecasts and dispatch, resource allocation, and grid management decisions that affect how networks actually operate. This is applied optimisation work. You'll formulate constrained optimisation problems, implement algorithms, and build systems that run in real-time or near-real-time operational contexts. You'll work closely with the rest of the Grid Modelling team to translate network physics into optimisation constraints and get solutions into production. What you'll do - Develop powerflow engines for grid modelling and forecasting - Solve constrained optimisation problems related to grid operations, resource dispatch, and network management - Design optimisation solutions that balance multiple objectives (safety, efficiency, customer impact, operational constraints) - Collaborate with others in the grid modeling team to formulate network models and constraints as optimisation problems - Build scalable optimisation solutions that perform in real-time or near-real-time operational contexts - Establish best practices for optimisation model development, validation, and monitoring - Contribute to technical strategy for data science, optimisation capabilities and future applications Qualifications - Powerflow and/or optimisation expertise - Deep experience with one or both of: - AC optimal powerflow (AC-OPF) calculations, including the use of key open-source packages such as OpenDSS, pandapower and lf-energy - Constrained optimisation, operations research, or similar fields (linear programming, convex optimisation, mixed-integer programming, familiarity with optimisation solvers and frameworks such as Pyomo, CBC, Gurobi, CPLEX, OR-Tools, etc.) - Data science foundations: Statistical modeling, numerical programming, algorithm design, data analysis - Senior/Staff level experience: 5+ years in data science/ML/optimisation roles with demonstrated impact - Python proficiency: Capable of writing quality code for optimisation algorithms and data analysis; familiar with architectural principles, system design, version control, testing practices, code review, CI/CD Requirements - Grid domain knowledge (electrical networks, power systems, operational constraints) - Experience with market dispatch, energy economics, or resource scheduling problems - Real-time or near-real-time optimisation system experience - Understanding of DER integration challenges and VPP operations - Experience in highly parametric statistical model fitting, e.g. state estimation for energy networks - Experience with optimisation in high-performance contexts, e.g. use of metaheuristics, HPC - Experience in load forecasting - Ability to work with customers to incorporate their existing forecasts into your own calculations - Software engineering depth (system design, testing, deployment, MLOps) - Familiarity with Databricks - Familiarity with data cleaning and data exploration Benefits - $160k–$220k depending on experience, plus equity - Remote-first, with head office in Sydney - A talented team of engineers, data scientists, and power systems specialists working on hard problems that matter Sound interesting? We'd love to hear from you! Apply directly and we'll be in touch shortly.

• Own technical direction for your squad, facilitating architectural decisions and ensuring alignment with platform strategy • Drive delivery outcomes, ensuring your squad ships high-quality work on cadence while managing technical risk • Establish and maintain engineering standards: code quality, testing practices, documentation • Unblock team members through hands-on contribution, code review, and technical guidance • Collaborate with Product and Design to translate requirements into well-scoped technical work • Identify and address technical debt, balancing short-term delivery with long-term system health • Mentor engineers in your squad, fostering technical growth and sound engineering judgment • Contribute to engineering-wide technical strategy and architectural decisions • (Optional) Manage and develop engineers, including hiring, performance management, career development, and day-to-day support

Role Description We’re hiring a Senior Product Manager to own one of Gridsight’s core product squads – the team building our real-time machine-to-machine grid constraint management and DER control capabilities. This is a deeply technical product role with a strong customer-facing dimension. The products this team builds run in real time on live utility networks, are co-developed with major utilities, and are expanding across multiple markets. You’ll own the product end-to-end – roadmap, customer engagements, implementation frameworks, and the day-to-day product leadership the team needs to execute. What You'll Do - Own the team’s product roadmap end-to-end – sequencing capabilities and maintaining alignment between engineering direction and commercial priorities across a maturing, technically complex product suite. - Lead the productisation of core capabilities – turning co-development opportunities into replicable, scalable products deployed across multiple utilities. - Be the face of the product in customer engagements relating to our machine-to-machine, real-time products – pre-sales discovery, implementation workshops, and co-development sessions across Australian and US utility customers. - Define and own implementation frameworks – standardising how our real-time products are deployed, configured, and validated for new customers. - Manage competing customer priorities across a two-market portfolio – finding common ground across Australian and US utilities and driving alignment on shared platform approaches. - Work closely with a highly capable engineering team to break complex capabilities into clearly defined, well-sequenced work. Qualifications - 5+ years in product management, product ownership, or a closely adjacent role. - Demonstrated ability to own complex, technical B2B products – ideally machine-to-machine or infrastructure platform products – end-to-end. - Experience leading technical customer workshops and managing co-development engagements with external organisations. - The ability to manage competing priorities across multiple customers, finding shared approaches that serve the platform. - Strong technical literacy – able to engage deeply with engineering discussions, ask the right questions and make sound product trade-offs. - Experience in a high-growth startup or scale-up where structure needs to be created, not inherited. Requirements - Background in energy, grid technology, utilities, telecommunications, or adjacent infrastructure domains. - Familiarity with power systems concepts – constraint management, DER, or network modelling. - Experience building repeatable implementation playbooks for technically complex enterprise products. - Exposure to real-time and/or machine-to-machine product design. Benefits - Competitive salary and equity package - Remote-first, with head office in Sydney - A talented team of product managers, engineers, data scientists, and power systems specialists working on hard problems that matter

Role Description We're hiring a Staff Platform Engineer to build the foundations that let every product squad at Gridsight ship faster and with greater confidence. You'll work across the engineering organisation — identifying the cross-cutting problems that slow squads down and solving them once, well. That might be observability, deployment pipelines, environment management, test infrastructure, or emerging areas like AI-assisted developer tooling. Wherever the leverage is, that's where you'll be. We're building an engineering culture where AI-assisted development is the norm, not the exception. We expect our engineers to be actively using agentic coding tools and LLM-assisted workflows to move faster, think bigger, and deliver more. If you're already working this way — or you're the kind of engineer who's itching to — you'll fit right in. What You'll Do - Identify and solve the cross-cutting platform problems that prevent product squads from shipping faster and with confidence - Build and operate observability platforms — metrics, tracing, logging, alerting — that give product teams and on-call engineers clear, actionable visibility into system health - Evolve our deployment automation, release management, and infrastructure-as-code; tackle environment management and test infrastructure head-on to reduce lead time and tighten CI feedback loops - Architect infrastructure that's secure, cost-effective, and scalable across multi-tenant, multi-region deployments — and proactively pay down tech debt before it bites - Bring platform engineering standards into our data layer (dbt, Databricks): CI/CD, automated testing, environment promotion, observability - Act as a culture carrier for platform and reliability engineering — mentoring engineers across squads, sharing patterns, and shifting how the broader engineering organisation thinks about reliability and developer experience - Treat internal developers as customers: seek feedback, measure satisfaction, iterate on tooling based on real friction Qualifications - 6+ years of software engineering experience with demonstrated impact at Staff level in platform, infrastructure, or SRE domains - Deep cloud infrastructure experience at production scale — compute, networking, storage, IAM, cost management — with strong infrastructure-as-code and container orchestration skills (AWS and Terraform preferred) - Proven track record building and operating observability platforms (metrics, tracing, logging, alerting) at meaningful scale - Strong software engineering fundamentals: clean architecture, testing, version control, code review - A track record of defining systems and practices, not just working within them — you set technical direction, form strong opinions grounded in experience, and drive outcomes without close direction - Demonstrated experience as an enabling function within a product engineering organisation — reducing cognitive load on product teams, building capabilities they adopt willingly, and knowing when to consult, guide, or step back - Fluency in AI-assisted development tooling — you're already using agentic coding tools or LLM-assisted workflows to accelerate your work Requirements - SRE background: SLOs, error budgets, incident management, chaos engineering, war games - Experience building internal developer platforms or PaaS capabilities with a strong focus on DX - Familiarity with data platform technologies (Databricks, Spark, dbt) and their infrastructure requirements - Experience with authentication and identity patterns (Auth0, Azure AD, SAML/SSO, OIDC) in multi-tenant environments - Contributions to open-source projects or technical communities - Experience in energy, utilities, or infrastructure technology Benefits - Competitive salary and equity package - Remote-first, with head office in Sydney - A talented team of engineers, data scientists, and power systems specialists working on hard problems that matter

Role Description Our Technical Business Analysts own data integration with our customers, ensuring they get value from Gridsight's platform quickly and seamlessly. This is equal parts customer-facing and technical. You'll work directly with utility customers to help them understand what data we need, review what they send, give feedback on issues, and get it into the platform. You'll spend roughly half your time in conversations with customers and half heads-down wrangling data, and configuring the system. What You'll Do - Work directly with utility customers to help them understand what data Gridsight requires, in what format, and how to provide it. - Review incoming customer data against expected schemas and quality standards, providing clear and constructive feedback on issues. - Onboard customer data into the platform using our tooling and workflows. - Identify and act on opportunities to improve our internal tooling, automating manual steps, improving validation, and making the data onboarding process more efficient, high quality and repeatable. - Drive customer data deliveries to completion — following up, unblocking, and maintaining momentum through the implementation process. - Manage complex customer situations with composure: unrealistic timelines, incomplete data, shifting priorities, and competing demands. - Identify and act on opportunities to automate manual steps, improve tooling, and make the data onboarding process more efficient and repeatable. Qualifications - Strong communication skills — you can explain technical data requirements to non-technical people, give constructive feedback, and manage expectations with confidence. - Proactive and self-directed — you see what needs doing and drive it to completion without close supervision. - Experience using SQL to analyse, validate, and wrangle messy datasets. - Experience in customer-facing or consulting-style technical roles with external stakeholder management. - Comfort with ambiguity — customer data environments are inconsistent and varied, and there won't always be a playbook. - Ability to manage your own time and priorities across multiple concurrent customer engagements. - 3+ years of professional experience in technical business analyst roles, data engineering, data analysis, technical consulting, or a similar role involving both technical and stakeholder-facing work. What Would Set You Apart - A track record of improving processes — automating manual work, building internal tools, or introducing better ways of working. - Experience with dbt or similar ELT frameworks, and exposure to working within data pipelines. - Expertise in leveraging AI-assisted development tooling. - Experience in energy, utilities, or infrastructure domains. Benefits - Competitive salary and equity package. - Remote-first, with head office in Sydney. - A talented team working on hard problems that matter. - A unique culture built around dialogue.

Role Description Our Customer Data Engineers own data integration with our customers, ensuring they get value from Gridsight's platform quickly and seamlessly. This is equal parts customer-facing and technical. You'll work directly with utility customers to help them understand what data we need, review what they send, give feedback on issues, and get it into the platform. You'll spend roughly half your time in conversations with customers and half heads-down wrangling data, running transforms, and configuring the system. What makes this role distinctive is where it's heading. We're continuously building better tooling to streamline data onboarding, and we want someone who accelerates that shift. From day one, we expect you to approach the work with a tool-first mindset — questioning manual steps, reaching for automation, and helping us develop internal products that make it a faster, more repeatable process. Over time, the role can grow in two directions: deeper into product engineering, or deeper into customer ownership and leadership. We'll support whichever direction plays to your strengths. Qualifications - Strong communication skills — you can explain technical data requirements to non-technical people, give constructive feedback, and manage expectations with confidence. - Proactive and self-directed — you see what needs doing and drive it to completion without close supervision. - Strong SQL skills with demonstrated ability to analyse, validate, and wrangle messy datasets. - Experience with dbt or similar ELT frameworks, and exposure to working within data pipelines. - Experience in customer-facing or consulting-style technical roles with external stakeholder management. - Comfort with ambiguity — customer data environments are inconsistent and varied, and there won't always be a playbook. - Ability to manage your own time and priorities across multiple concurrent customer engagements. - 3+ years of professional experience in data engineering, data analysis, technical consulting, or a similar role involving both technical and stakeholder-facing work. Requirements - Work directly with utility customers to help them understand what data Gridsight requires, in what format, and how to provide it. - Review incoming customer data against expected schemas and quality standards, providing clear and constructive feedback on issues. - Onboard customer data into the platform using tooling and transformation workflows. - Identify and act on opportunities to improve our internal tooling, automating manual steps, improving validation, and making the data onboarding process more efficient, high quality and repeatable. - Drive customer data deliveries to completion — following up, unblocking, and maintaining momentum through the implementation process. - Manage complex customer situations with composure: unrealistic timelines, incomplete data, shifting priorities, and competing demands. - Identify and act on opportunities to automate manual steps, improve tooling, and make the data onboarding process more efficient and repeatable. What Would Set You Apart - A track record of improving processes — automating manual work, building internal tools, or introducing better ways of working. - Expertise in leveraging AI-assisted development tooling. - Experience in energy, utilities, or infrastructure domains. - Experience with data quality frameworks, monitoring, or observability. Benefits - Competitive salary and equity package. - Remote-first, with head office in Sydney. - A talented team of engineers, data scientists, and power systems specialists working on hard problems that matter. - A role with clear growth pathways into product and tooling, or deeper customer ownership.

Role Description We're hiring a Senior to Staff-level Data Engineer to build and evolve the data layer that powers our grid analytics products. This is a hands-on data engineering role. You'll design pipelines, write transformations, and ship data that downstream consumers — data scientists, product engineers, and analysts — depend on daily. - Design, build, and maintain scalable data pipelines that transform and serve data for analytics and platform features - Ensure data quality, reliability, and observability across the pipelines and models you own - Collaborate with Data Science, Product Management, Software Engineering and Design to understand domain requirements and translate them into robust data structures and systems - Establish data engineering standards — modelling conventions, testing practices, documentation, and observability - Identify and address data technical debt, particularly where poor abstraction is creating complexity downstream - Mentor other engineers on data modelling, pipeline design, and transformation architecture Qualifications - 5+ years of data engineering experience with demonstrated impact at Senior or Staff level - Strong experience building and maintaining production data pipelines at scale - Hands-on experience designing layered transformation architectures (staging, intermediate, mart patterns) in production - Deep knowledge of modern data stack technologies (orchestration, transformation, storage, and streaming) and the Data Engineering lifecycle - Solid data modelling fundamentals — dimensional modelling (Kimball), relational theory, and a clear sense of when to apply different techniques - Experience with dbt or similar transformation frameworks - Solid software engineering fundamentals: version control, testing, code review, CI/CD - Fluency with AI-assisted development tools and workflows - Experience working closely with downstream consumers and designing data that serves their needs - A track record of bringing structure and clarity to complex or messy data landscapes Requirements - Experience in energy, utilities, or grid technology - Experience building data products with defined consumers, SLAs, and quality contracts - Time-series data or operational analytics experience - Background in data mesh principles or domain-oriented data architecture - Experience with distributed systems or stream processing - Experience with modern data orchestration tools (Airflow, Dagster, Prefect) - Cloud data infrastructure depth (AWS, GCP, or Azure) Benefits - Competitive salary and equity package - Remote-first, with head office in Sydney - A talented team of engineers, data scientists, and power systems specialists working on hard problems that matter

Role Description We're hiring a Senior or Staff-level Software Engineer to join our engineering team and help build the next generation of our platform. You'll work across the stack, owning features end-to-end - from understanding the problem through to shipping and iterating in production. The work spans our grid analytics platform: building the software that helps utilities understand, operate, and optimise their networks as the energy transition accelerates. We're building an engineering culture where AI-assisted development is the norm, not the exception. We expect our engineers to be actively using agentic coding tools and LLM-assisted workflows to move faster, think bigger, and deliver more. If you're already working this way - or you're the kind of engineer who's itching to - you'll fit right in. What You'll Do - Build and ship high-impact software features across the Gridsight platform - Own features end-to-end: from understanding the problem through to shipping and iterating in production - Make sound trade-offs between speed, quality, and scope to maximise product outcomes - Collaborate with product, data science, and data engineering to shape how our platform evolves - Leverage AI-assisted development tooling to accelerate delivery and raise the bar on what a small team can ship - Contribute to engineering culture: code quality, testing, observability, and knowledge sharing Qualifications - 4–8+ years of software engineering experience with a track record of delivering impact at Senior or Staff level - Strong engineering fundamentals: clean architecture, testing practices, code review, CI/CD — in service of shipping things that matter - Experience shipping user-facing product features in production - Fluency in the use of AI-assisted development tools — you're already using agentic coding tools, LLM-assisted workflows, or similar to accelerate your work - Strong ownership and a bias to action — you take things from idea to working software without waiting to be told Requirements - Experience building LLM-integrated product features in production - Frontend development experience with modern frameworks (React or similar) - Experience in energy, utilities, or infrastructure technology - Distributed systems or data engineering experience Benefits - Competitive salary and equity package - Remote-first, with head office in Sydney - A talented team of engineers, data scientists, and power systems specialists working on hard problems that matter