Role Description We are looking for an AI Platform Developer Senior to help shape the future of how developers build with AI. This role sits at the intersection of infrastructure, tooling, and developer experience, focused on building a scalable platform for developing, deploying, and maintaining AI applications. You will work within a modern cloud-based environment, enabling internal teams and external developers to leverage AI technologies to build code assistants, autonomous agents, and full-stack AI applications. If you are passionate about making AI accessible, efficient, and secure, this is an opportunity to make a lasting impact. What You’ll Get to Do - Design and build scalable infrastructure supporting AI workloads, including inference, training, and fine-tuning within a cloud-native, multi-tenant platform. - Develop tools, APIs, and libraries that simplify the development and deployment of AI and LLM-based applications. - Integrate and optimize large language models (LLMs), retrieval-augmented generation (RAG) pipelines, vector databases, embedding stores, and multimodal systems. - Implement MLOps best practices for model versioning, deployment, monitoring, and performance optimization. - Collaborate with Engineering, Product, and Research teams to deliver AI-powered capabilities that enhance developer experiences. - Ensure platform reliability, scalability, security, and responsible AI practices. - Evaluate emerging AI tools, frameworks, and technologies for platform adoption and innovation. - Contribute to architectural decisions that support long-term platform growth and maintainability. - Drive continuous improvements in developer productivity and platform capabilities. Qualifications - Bachelor’s degree in Computer Science, Data Science, or a related field. - 6+ years of software engineering experience, including 4+ years focused on AI/ML infrastructure or platform development. - Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform and their machine learning services. - Familiarity with cloud-native AI platforms such as Replit, Vercel, LangChain, or similar technologies. - Strong experience building distributed systems and scalable compute infrastructure using technologies such as Kubernetes and serverless architectures. - Solid understanding of LLMs, vector databases, RAG pipelines, and model fine-tuning workflows. - Strong programming skills in Python; experience with Go, TypeScript, or JavaScript is an asset. - Experience with MLOps platforms and practices such as MLflow, Weights & Biases, Azure ML, or Vertex AI. - Strong understanding of cloud security, observability, and performance engineering principles. - Excellent problem-solving, collaboration, and communication skills. What Would Make You Stand Out - Direct experience integrating AI capabilities into developer platforms, IDEs, code assistants, or copilots. - Experience working with cloud-native AI development platforms such as Replit, Vercel, LangChain, or similar solutions. - Hands-on experience with LLMs, vector databases, RAG pipelines, and model fine-tuning. - Contributions to open-source AI tools, frameworks, or platforms. - Experience optimizing LLMs for low-latency inference in browser or edge computing environments. - Strong product intuition and a track record of building tools that developers love. - Passion for democratizing AI and enabling builders of all skill levels to succeed. Benefits - Excellent time away from work programs. - Comprehensive wellness initiatives. - Recognition through competitive pay and benefits. - Opportunities for personal and professional growth. - Commitment to community impact, including volunteer days and our charity, Dayforce Cares.

• Develop and maintain robust Power BI, Power Apps, and Power Automate solutions that meet the government’s requirements. • Conduct analysis of requirements to identify appropriate Power Platform solutions. • Conduct comprehensive interviews and workshops with government stakeholders to elicit, clarify, and document business requirements. • Analyze and document requirements, ensuring a clear understanding of the desired outcomes and functional specifications. • Identify gaps or inconsistencies in requirements and work collaboratively with stakeholders to resolve them. • Design, develop, and customize Power BI reports and dashboards to visualize data effectively. • Build Power Apps solutions that address specific government processes, incorporating intuitive user interfaces and seamless data integration. • Design and develop SharePoint pages, templates, and sites using HTML, CSS, JavaScript, or any other approved programming language. • Build SP list and library forms using Power Apps and Power Automate. • Develop and customize document libraries using content types and site columns. • Integrate SharePoint workflows with external systems and data sources to automate data retrieval and updates. • Conduct testing and debugging of workflows to ensure accuracy and reliability.

• Manage and support a multi-site on-premises Oracle Endeca environment, with dedicated applications and MDEX engines for each site. • Administer, monitor, and optimize MDEX engines, DGraph, Forge pipelines, and search/navigation configurations. • Analyze and resolve search relevance, navigation, facets, and product discovery issues across multiple sites. • Monitor and tune query performance, indexing, and system resource usage to ensure the best customer experience. • Investigate and resolve production incidents related to search availability, indexing failures, performance degradation, and application integrations. • Design, maintain, and troubleshoot data ingestion pipelines based on Forge and custom ETL processes from flat files. • Manage deployments, versioning, and releases using GitLab (custom cartridges, scripts, configurations). • Work with Squid proxy infrastructure for cache troubleshooting, routing, latency, and availability between the application and Endeca. • Execute Endeca index builds, deployments, rollbacks, and validations in a controlled production environment. • Develop and maintain operational runbooks, support documentation, deployment procedures, and disaster recovery plans.

Role Description Managing business expenses shouldn’t be a guessing game. Yet many SMEs still lack clear cash flow visibility and spend control. At Budgetly, we’re changing that. We’re building an AI-first platform that simplifies expense management and helps businesses make better financial decisions, faster. The goal is simple: help you spend smarter, save time, and grow profitably. Six months ago, “agentic engineering” felt novel. Today, it’s rapidly becoming the default way teams ship software. Most companies are using AI to make engineers type faster. We’re building something more ambitious: - We’re building an AI-first delivery system where agents ship product features end-to-end — and engineers build the platform (the harness) that makes it safe, reliable, and scalable. - If this works, feature delivery scales with product ambition, not headcount. In this role, you’ll build that harness: - Agent runtimes & execution loops (plan → act → observe → reflect; retries; stop conditions) - Agentic loops & feedback loops that convert outcomes into improvements (evals, regressions, learnings) - Tooling & skills (MCP/tool integration, internal APIs, secure credentials, sandboxes) - Governance (permissions, policy, human-in-the-loop gates, audit trails) - Observability (traces, cost attribution, failure taxonomies, runbooks) - Evaluation harnesses (scenario suites, trajectory scoring, tool-arg correctness, “non-deterministic unit tests”) What success looks like in ~12 months: - A managed agent platform that product can rely on for meaningful, customer-facing delivery - Agent workflows ship features with high repeatability, not “poke-and-hope” - Clear quality gates: eval harnesses, review agents, regression suites, and rollout controls - Engineers spend less time in the loop and on reviews and more on improving the factory (reliability, speed, safety) This isn’t a traditional senior engineering role. You won’t spend most of your time implementing product features directly. Your time will roughly split: - 50% building and evolving agent harnesses: orchestration, toolchains, approvals, secure execution, managed agents - 50% reviewing and improving outputs: tracing failures, improving prompts/steering, tightening eval harnesses, reducing loop count Concretely, you’ll: - Design and implement agentic workflows that take a requirement from spec → code → review → deploy - Build agentic loops that turn mistakes into system-level improvements (not one-off fixes) - Develop evaluation harnesses (offline + CI) to detect regressions in behavior, not just tests in code - Define and maintain review gates (human-in-the-loop + automated reviewers) for risky changes - Improve tool reliability: schemas, typed tool interfaces, retries, timeouts, safety checks - Build platform capabilities for managed agents: long-running sessions, checkpoints, state/memory boundaries, and recovery - Evolve the platform architecture (TypeScript, serverless architecture, shared codebase) with an eye for simplicity and maintainability - Partner with Product to reduce ambiguity and translate intent into testable, evaluable spec Qualifications - Strength in systems thinking for agent harnesses and loops - Ability to design the execution harness around agents: feedback loops, evaluation strategy, safety constraints, and the “glue code” that makes autonomy safe in production - Engineering taste: ability to judge agent-generated code for conventions, simplicity, correctness, maintainability, security - Strong TypeScript and React experience in production environments - Experience shipping real software to real users (not just prototypes) - Ability to read a codebase and quickly identify its patterns, conventions, and architecture - Comfortable working in ambiguity and turning fuzzy intent into clear acceptance criteria + evals - Familiarity with agent tooling concepts: tool calling, MCP/tool integration, guardrails, evals, tracing/observability, and permissioning - Nice to have: AWS serverless experience (CDK, Lambda, DynamoDB) Requirements - Strong TypeScript and React experience in production environments - Experience shipping real software to real users (not just prototypes) - Ability to read a codebase and quickly identify its patterns, conventions, and architecture - Comfortable working in ambiguity and turning fuzzy intent into clear acceptance criteria + evals - Familiarity with agent tooling concepts: tool calling, MCP/tool integration, guardrails, evals, tracing/observability, and permissioning - Nice to have: AWS serverless experience (CDK, Lambda, DynamoDB) Benefits - Fully remote (work from anywhere in Australia) - 5 weeks annual leave and flexible working - Monthly Wellness Budget (mental & physical health) - Employee share options (ESOP) for all team members Company Description We’re guided by trust, respect, and ownership. Our values, Embrace Change, Carte Blanche, Find Wisdom in Data, and We All “Own It”, shape how we work. We welcome applications from all backgrounds, abilities, and identities. We value diversity and believe that it enhances our creativity, innovation, and overall success. Join us in creating a workplace where everyone can thrive. Compensation: AUD 140000 - AUD 170000 yearly