R Full Stack Developer, Shiny & AI

Job Type: Full-time or Part-time Location : Onsite, Hybrid or Remote Compensation: Based on demonstrated skill, experience and level of responsibility, in line with SUSNEO's internal compensation scale. Company OverviewSUSNEO is a data-first sustainability technology company developing software and managed data solutions that help organisations collect, structure, analyse and report complex sustainability, carbon, ESG and operational data. Our core platform is built primarily using R, Shiny and the golem framework, with R6 classes, SQL databases, APIs, JSON integrations and Git-based version control. Our applications are deployed using DigitalOcean, with CI/CD through GitHub Actions. We also work with AWS services including S3 and RDS/MariaDB, and use Python and LLMs within selected data-engineering and AI workflows. We are increasingly developing agent-based and multi-agent workflows that interact with SQL databases, APIs and structured enterprise data. About the RoleWe are looking for an experienced developer who can contribute not simply as an R programmer, but as a software engineer working on a live production data platform. You will help develop, maintain and improve R Shiny applications, backend architecture, database integrations, APIs, data workflows and emerging AI functionality. The right candidate should be comfortable taking ownership of technical problems, understanding an existing production codebase, debugging independently and building maintainable, scalable solutions. Key ResponsibilitiesDevelop and maintain production-level R Shiny applications.Work with the golem framework and R6 classes.Build modular, reusable and maintainable application components.Debug, refactor and optimise existing Shiny applications.Write and optimise SQL queries and work with MariaDB/MySQL or similar relational databases.Work with database schemas, joins, transformations and large datasets.Integrate applications with REST APIs and third-party services.Read, create, validate and transform JSON, including nested JSON structures.Manage code using Git and GitHub.Develop and maintain GitHub Actions CI/CD pipelines.Deploy and troubleshoot applications on DigitalOcean.Work with AWS services including S3 and RDS/MariaDB where required.Improve application performance, reliability, logging and error handling.Write clean, documented and production-level code.Apply appropriate security, authentication, permissions and secrets-management practices.Contribute to testing and code-quality processes.Support development of LLM-powered features, AI chatbots and data-contextualisation workflows.Contribute to agent and multi-agent workflows that interact with SQL databases, APIs and structured data.Support Python-based data-engineering and AI workflows.Required SkillsStrong proficiency in R.Strong experience with R Shiny.Experience using the golem framework.Practical experience with R6 classes.Strong understanding of reactive programming and Shiny architecture.Strong debugging and problem-solving skills.Strong SQL skills.Experience with relational databases such as MariaDB/MySQL.Strong working knowledge of JSON.Experience consuming or building REST APIs.Experience with Git and GitHub.Experience with CI/CD, preferably GitHub Actions.Experience deploying and supporting production web applications.Strong understanding of software-engineering principles including modularity, testing, maintainability and documentation.Experience creating data visualisations using packages such as ggplot2, echarts4r or plotly.Ability to work independently and take ownership of technical problems.Preferred SkillsThe following are advantageous but not essential: 3+ years of professional R Shiny development experience.Experience building full production applications rather than dashboards or prototypes alone.Docker and Linux experience.DigitalOcean or comparable cloud infrastructure experience.AWS experience.Python experience.Databricks experience, including Databricks SQL or data-engineering workflows.Experience with automated testing using testthat or shinytest2.Experience with authentication, authorisation and web-application security.Experience with application monitoring and performance optimisation.AI / Agent ExperienceExperience in any of the following would be particularly valuable: LLM API integrations.R packages such as ellmer or equivalent tools.Tool/function calling.Structured outputs and JSON schemas.Agent-based workflows.Multi-agent systems and orchestration.Agents interacting with SQL databases.Natural-language-to-SQL workflows.Validation and guardrails for AI-generated SQL.Agent workflows covering data retrieval, validation, analysis and reporting.Context management and LLM evaluation.AI-enabled data engineering.Experience in sustainability, carbon or ESG data is useful but not required. AI and Coding PolicySUSNEO actively uses AI and LLMs within selected products, data-engineering workflows and platform functionality. However, we currently do not permit AI-integrated coding assistance within our software-development environment. Developers are expected to understand, write, review and debug the code they contribute themselves. Candidates should therefore be comfortable developing without reliance on AI coding agents, AI code-generation assistants or AI-integrated IDE support. This does not mean SUSNEO is anti-AI. AI is an important part of our technology roadmap; the distinction is that developers must retain direct understanding, ownership and accountability for production code. Interview ProcessThe recruitment process will include a live technical coding assessment completed without AI-assisted coding tools. Candidates may be asked to: Read and explain existing R code.Debug an R Shiny issue.Modify or develop Shiny functionality.Work with reactive logic or R6 classes.Write SQL queries.Work with JSON or API responses.Explain application architecture or deployment decisions.Discuss testing, security and productionisation.Candidates with relevant AI experience may also be asked to discuss agent workflows, multi-agent systems, SQL-connected AI agents, structured outputs, Databricks and LLM integrations. We are interested in how candidates reason, debug, structure solutions and make engineering decisions, rather than whether they memorise every syntax element. CompensationCompensation will be based on: Demonstrated technical ability.Relevant experience.R/Shiny and software-engineering capability.SQL and data-engineering skills.Level of independence.Ability to take ownership of production systems.Relevant cloud, AI or agent-workflow experience.Successful candidates will be positioned on SUSNEO's internal compensation scale following the technical assessment. What We OfferWork on a growing production technology platform.Exposure to complex real-world datasets and engineering problems.Work across R Shiny, SQL, APIs, Python, cloud infrastructure and AI systems.Exposure to agentic and multi-agent architectures.Significant ownership and influence over platform development.A maker mindset with strong emphasis on self-direction and practical problem-solving.Continuous learning and exposure to emerging technologies.