This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Process Forward Deployed Engineer based in Australia. This is a high-impact engineering role focused on bringing AI-powered process automation into enterprise production environments. You&#x2019;ll own customer deployments from initial workflow setup through measurable improvement and successful handoff. The role combines hands-on software engineering, distributed systems, AI agents, workflow orchestration, and customer-facing technical leadership. You&#x2019;ll work across Java services and React interfaces while configuring platforms, debugging integrations, and developing custom solutions. Your work will directly influence product evolution, deployment practices, and reusable engineering patterns. The environment is global, remote, collaborative, and designed for engineers who are comfortable operating with significant autonomy and ambiguity. Accountabilities <ul><li>Own the end-to-end deployment journey, from the initial process file through a production workflow that continuously improves based on measurable results. </li><li>Establish successful customer outcomes, including achieving an operational workflow and active improvement loop within the initial deployment period. </li><li>Build and customize product capabilities, including features, AI agents, and skill files, while addressing bugs and technical limitations encountered in real-world deployments. </li><li>Configure platform environments, including clusters and integrations, and troubleshoot complex failures across distributed systems and enterprise technology stacks. </li><li>Develop custom agents and integrations when standard platform capabilities do not adequately address customer requirements. </li><li>Work closely with engineering, architecture, business, and customer stakeholders to drive organizational adoption and turn initial deployments into sustainable capabilities. </li><li>Capture lessons learned, document successful implementation patterns, and build a repeatable deployment playbook that improves future implementations. </li><li>Train and enable customer teams so they can independently operate the solution and act on ongoing improvement results after the handoff. </li><li>Contribute engineering insights from customer deployments directly back into product development and platform evolution. </li><li>Travel occasionally when required to support customer or team engagements. </li></ul>Requirements <ul><li>Proven experience delivering and operating software in enterprise production environments, with a strong understanding of governance, resilience, reliability, and operational requirements at scale. </li><li>Strong software engineering capabilities, including the ability to debug integrations, build custom agents against APIs or legacy systems, configure platform clusters, and work across distributed systems. </li><li>Experience working with Java-based services and React interfaces, or the ability to quickly operate across comparable technology stacks. </li><li>Practical production experience with AI technologies, including AI-powered applications, prompt engineering, context management, agent testing, and evaluating integration trade-offs. </li><li>Ability to understand and explain generated BPMN workflows and technical concepts to both engineering teams and business stakeholders. </li><li>Strong customer and stakeholder communication skills, with the ability to adapt technical discussions for engineering, architecture, and business leadership audiences. </li><li>Demonstrated ability to operate effectively in ambiguous environments, make sound technical and operational decisions, and document emerging best practices. </li><li>Experience working in customer-facing engineering, solutions engineering, or professional services environments is a plus. </li><li>Familiarity with regulated industries such as financial services, healthcare, or insurance is advantageous. </li><li>Production experience with agentic systems or AI-integrated workflows is a plus. </li><li>Contributions to shared platforms or open-source projects are valued. </li><li>Ability and willingness to use the product as part of the role. </li><li>Willingness to travel occasionally as required. </li></ul>Benefits <ul><li>Fully remote and flexible working environment. </li><li>Home office budget and support for coworking spaces. </li><li>Flexible time off. </li><li>Competitive, location-based compensation with transparent salary structures. </li><li>Equity through a Virtual Stock Option Plan where applicable. </li><li>Locally tailored healthcare benefits. </li><li>Global mental wellbeing support through Modern Health. </li><li>Live Well Lifestyle Spending Account supporting health, family, personal interests, experiences, and financial wellbeing, launching in 2026 and scaling to &#x20AC;1,000 annually from 2027. </li><li>Retirement and pension plans, often including company contributions. </li><li>Life and disability insurance where applicable. </li><li>Annual learning and development budget of up to $/&#x20AC;/&#xA3;1,000 for courses, certifications, books, and other self-directed learning. </li><li>Annual company kickoff events, team offsites, local gatherings, and connection budgets that support meaningful in-person collaboration. </li><li>Inclusive global environment with opportunities to work alongside diverse teams and cultures. </li></ul>How Jobgether Works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role&apos;s core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

AI Process Forward Deployed Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Warehouse Engineer based in Australia. This role offers the opportunity to shape the data infrastructure supporting a high-growth technology platform focused on online security and fraud detection. You will design and optimize scalable data warehouses, reliable pipelines, and modern ELT processes that enable analytics and data-driven decision-making. Working closely with data scientists, analysts, and engineers, you will transform complex data into trusted and actionable insights. The position combines hands-on engineering with opportunities to improve performance, reliability, cost efficiency, and developer productivity. You will work with modern cloud technologies including ClickHouse, Redshift, AWS, Kafka, dbt, and Prefect. This is a strong opportunity for an autonomous data engineer who enjoys solving complex problems in a globally distributed, fully remote environment. Accountabilities <ul><li>Architect, build, and maintain scalable, high-performance data warehouse solutions that support analytics and operational needs.</li><li>Develop reliable, well-documented data pipelines and ELT processes while maintaining strong standards for data quality and consistency.</li><li>Optimize data warehouse performance through query optimization, partitioning, indexing, and other performance-tuning techniques.</li><li>Partner with data analysts and data scientists to transform raw data into actionable analytics and support machine learning initiatives.</li><li>Monitor, troubleshoot, and continuously improve data warehouse infrastructure while balancing performance, reliability, and cost efficiency.</li><li>Establish and promote best practices for clean, well-structured, reliable, and accessible data.</li><li>Work with modern cloud-based data warehouses such as ClickHouse and integrate data platforms with other cloud services.</li><li>Contribute to developer-facing data tools and solutions that empower engineering and other technical teams.</li><li>Support data transformation and modeling initiatives using tools such as dbt and SQL.</li><li>Contribute to automation, testing, version control, code reviews, and other software engineering practices across data systems.</li><li>Help improve the scalability, maintainability, and operational efficiency of the overall data platform. </li></ul>Requirements <ul><li>Extensive professional experience designing, implementing, and optimizing data warehouses in cloud environments such as AWS or GCP.</li><li>Strong hands-on expertise with data modeling and transformation tools, particularly dbt.</li><li>Excellent SQL skills and experience with modern columnar or cloud data warehouse technologies such as ClickHouse, Databricks, BigQuery, Snowflake, or Redshift.</li><li>Experience developing and managing data pipelines using orchestration tools such as Prefect or Airflow.</li><li>Solid understanding of data engineering principles, warehouse architecture, transformation, and data quality.</li><li>Strong software engineering fundamentals, including version control, code reviews, testing, automation, and maintainable development practices.</li><li>Experience working collaboratively with data scientists, analysts, engineers, and other cross-functional stakeholders.</li><li>Strong English communication skills for effective collaboration within a globally distributed remote team.</li><li>High degree of ownership, autonomy, and accountability, with the ability to work effectively in ambiguous environments.</li><li>Strong analytical and problem-solving skills, with a practical approach to troubleshooting and performance optimization.</li><li>Familiarity with business intelligence and visualization tools such as Apache Superset, Sigma, Tableau, or Looker is a plus.</li><li>Experience with infrastructure-as-code tools such as Terraform and a DevOps-oriented mindset is desirable.</li><li>Scripting or automation experience with Bash, Python, or Go is an advantage.</li><li>Experience with technologies such as Kafka, AWS, Terraform, and modern data visualization platforms is beneficial. </li></ul>Benefits <ul><li>Fully remote work arrangement within eligible hiring locations.</li><li>Opportunity to work on large-scale data infrastructure supporting a technology platform focused on online security and fraud detection.</li><li>Exposure to a modern technology stack including ClickHouse, Redshift, Confluent Kafka, dbt, Prefect, AWS, Terraform, Apache Superset, and Sigma.</li><li>Opportunity to collaborate with data scientists, analysts, engineers, and globally distributed technical teams.</li><li>High level of ownership and autonomy in a data engineering environment.</li><li>Opportunity to contribute to developer-facing tools and scalable data platform initiatives.</li><li>US-based compensation range of $152,000&#x2013;$205,000; compensation may vary by hiring location and is not directly applicable to all locations.</li><li>Fully remote international environment with team members distributed across multiple countries and time zones.</li><li>Visa sponsorship is not provided; candidates must be authorized to work from their home location.</li><li>Specific India-based salary, healthcare, retirement, paid time off, and other benefits were not specified in the source description. </li></ul>How Jobgether Works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role&apos;s core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Senior Data Warehouse Engineer

About Mutinex We&apos;re an early-stage B2B SaaS startup with a proven platform, big-name clients, and millions in revenue. We&apos;re not chasing unicorn status; we&apos;re building a sustainable, long-lasting business (think Bowhead Whale!). Mutinex is on a mission to build a universal business growth decision engine! It empowers marketing, media, agency, analytics, and finance teams to organise, analyse, and action data at scale, unlocking and optimising the true drivers of sustainable business growth.We&apos;re a hybrid team based in Sydney, Melbourne, and New York. We value communication, open-mindedness, and a culture of feedback. The RoleWe are looking for a Machine learning and Software Engineer to join our team at Mutinex, where you&apos;ll be a key contributor to help design, build, automate and optimise the infrastructure and tooling that powers our data science and product workflows.This is a software engineering role, applied to the data and machine learning domain. This hybrid role combines software engineering skills with machine learning engineering expertise to deliver automated, reliable, and observable ML pipelines that serve our customers globally. You&apos;ll have the opportunity to work across our tech stack, from infrastructure to internal tools, to deliver complete, end-to-end solutions. Role Responsibilities<ul><li>Predictive Modelling and Forecasting: Develop and refine time series models to power accurate forecasting and outcome comparisons. Enable data-driven customer decision-making by integrating predictions into planning workflows.</li><li>Optimisation Frameworks: Build and scale optimisation frameworks that solve complex, constraint-based problems to support customer decision making.</li><li>Backend API &amp; Database Development: Design and maintain scalable backend systems. Build APIs and database layers using frameworks like FastAPI and SQLAlchemy. Implement clean, testable code following modern software design principles and CI/CD best practices.</li><li>Cloud Infrastructure &amp; Orchestration: Architect event-driven systems using technologies like Cloud Run, Pub/Sub, and BigQuery. Manage parallel, multi-customer workloads with infrastructure-as-code and automated job orchestration to ensure reliability and scalability.</li></ul> What We&apos;re Looking For<ul><li>Software Engineer: You have experience building production systems and taking POCs to production. You&apos;re skilled in building APIs, CI/CD, testing, and deployment automation, and you apply solid engineering practices like clean, maintainable code. You&#x2019;re also familiar with modern cloud infrastructure (we use GCP), IaC tools like Pulumi or Terraform, and container technologies like Docker and Kubernetes.</li><li>Machine Learning &amp; Data-Driven Applications: You have a solid grasp of the machine learning lifecycle, strong Python skills, and hands-on experience with tools like scikit-learn, pandas, PyTorch, and TensorFlow.</li><li>Pragmatic Craftsmanship: You see software engineering as a craft and are passionate about building high-quality, reliable, and well-tested software that has meaningful impact on the business. You don&#x2019;t just write code that works; you write code that is clean, maintainable, and a pleasure for others to work with.</li><li>Curiosity: You&apos;re eager to learn, take on new challenges, and are interested in expanding your technical expertise and impact. You are not afraid to say you don&apos;t know and fill any knowledge-gap on the job.</li><li>Product Mindset: As a startup, we look for people who understand and help drive the bigger picture&#x2014;business goals and user needs. You think beyond coding, focusing on how your work advances the product and creates real value for customers.</li><li>Proactive Problem-Solver: You don&apos;t just fix bugs; you identify the root cause and improve the system to prevent future issues. You document past issues and propose clear solutions that go beyond your technical skills.</li></ul> Why work with us?<ul><li>Direct Customer Impact: Your work will directly impact the customer experience and marketing decision making.</li><li>Technical Challenges: Work on cutting-edge ML infrastructure problems at scale</li><li>Autonomy: Lead initiatives from design through implementation with minimal oversight</li><li>Growth: Opportunity to shape ML engineering practices across the organisation</li><li>Team: Work with experienced data scientists and engineers who are driven by impact and committed to doing great work.</li><li>ESOP: All staff receive equity (ESOP)</li><li>Parental Leave: We offer 12 weeks paid leave to primary caregiver and 6 weeks to secondary caregiver after 2 years in business</li><li>Annual Leave: You will receive 20 days base annual leave , +5 days after the first year, and +1 for each year after that up to 30 days total.</li><li>6 weeks work from anywhere: You are eligible to work 6 weeks anywhere in the world a year - just take your laptop and wifi and you&#x2019;re good to go!</li></ul> Ready to join us?If you&apos;re passionate about building data platforms and eager to make a big impact in a fast-growing startup, we&apos;d love to hear from you. Send us your resume and a brief cover letter explaining why you&apos;re excited about this opportunity.

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