Mindera

Engineer

• Deploy and support Viva Connections and Viva Amplify across large enterprise organisations
• Design and configure SharePoint Communication Sites and SharePoint News functionality
• Build and customise Viva Connections cards based on business requirements
• Develop custom cards using Quick Views, Card Views, and Adaptive Card Extensions (ACEs)
• Develop and customise solutions using SharePoint Framework (SPFx)
• Work closely with business and technical stakeholders to understand requirements and deliver scalable solutions
• Troubleshoot and optimise Viva and SharePoint solutions in enterprise environments

Senior Microsoft 365 / Viva Engineer

iOS Engineer

• Create fast, fluid, responsive and reliable mobile applications
• Participate in the whole development cycle using modern technologies, architectures and processes
• Work self-driven with little supervision toward a common team or company purpose
• Create fluid visual interactions and implement mobile user experience patterns
• Apply software craftsmanship and seek the best solutions
• Keep up with trends, architectures, ideas and technologies in the mobile ecosystem
• Share knowledge and lead by example
• Produce clean and organized code using software design patterns, architectural patterns and data structures
• Potentially travel 0%–15% depending on project and client needs

Senior iOS Developer

Backend Engineer

• Build software services and APIs using Python frameworks, ideally FastAPI
• Design and maintain secure cloud infrastructure from a software engineering perspective
• Handle core networking components including WAF and CDN
• Manage infrastructure as code using Terraform
• Deploy scalable services using Kubernetes, specifically AKS, and Docker
• Implement end-to-end data solutions
• Ensure data flows correctly across real-time architectures using Kafka/Kinesis and batch architectures
• Set technical direction and align core system designs with strategic goals
• Drive Python language and technology adoption across multiple teams
• Define and promote engineering, testing, quality, security, observability, and performance best practices
• Collaborate on CI/CD workflows and automated deployment pipelines
• Support and monitor critical production systems
• Lead resolution and post-mortem analysis of complex technical issues
• Drive continuous process improvement across Agile teams
• Work closely with leadership, including the CEO and COO, and clients
• Guide and teach others while collaborating with an agile team

Principal – Python Engineer

Software Engineer

• Work directly with engineering teams to embed AI-assisted and agentic development practices into daily workflows
• Coach teams on balancing engineering quality, security, and maintainability with AI-assisted development
• Partner with engineering leadership to improve delivery effectiveness and productivity through AI tooling, automation, and agent orchestration
• Build prototypes, examples, and reference implementations demonstrating agentic development patterns
• Help engineers develop effective prompting, validation, and review techniques
• Help teams measure the impact of AI-assisted engineering practices on software delivery outcomes
• Contribute to engineering practices, standards, and guidance
• Stay current with emerging agentic development techniques and identify opportunities for organizational adoption

AI Coach – Agentic Engineering

Full-stack Engineer

• Participate in all areas of delivery
• Mentor and inspire the development team by sharing knowledge, experience, and insights
• Own code from development through deployment and maintenance
• Diagnose production issues and devise solutions
• Contribute to solution design and implementation
• Challenge business requirements to deliver the best possible outcomes
• Drive adoption of new technologies to deliver business value
• Help shape the online technology roadmap and future technical direction
• Conduct technical interviews within the area of expertise
• Travel nationally and internationally according to project, client, and organizational needs, estimated at 0%-15%

Senior/Staff Java FullStack Developer

• Operate within a Platform Enablement team in the retail sector
• Look after capabilities shared across products and channels
• Design and evaluate scalable services and integrations
• Build and operate cloud-native solutions in AWS
• Apply architecture patterns while balancing product goals, security, reliability, and long-term system health
• Take ownership from design through production within Agile product teams
• Contribute to and influence technical decisions
• Mentor engineers through code reviews, pairing, and knowledge sharing
• Troubleshoot distributed systems and use observability to improve performance and reliability
• Focus on customer value and continuous improvement

Tech Lead – Contract

Data Scientist

• Lead consolidation of existing recommendation algorithms into a simpler, coherent recommendation capability
• Implement the client’s existing technical direction and agreed delivery plan
• Review recommendation approaches and rationalise duplication, inconsistency and unnecessary complexity
• Develop, improve and productionise recommendation models for customer and commercial use cases
• Own data and feature development, model development, evaluation, production implementation, monitoring, retraining and ongoing optimisation
• Develop scalable production workloads in Databricks using Python and PySpark
• Refactor exploratory or notebook-based Data Science code into maintainable production implementations
• Apply object-oriented design and software engineering principles to the recommendation codebase
• Create reusable and testable components for candidate generation, scoring, ranking, feature generation and evaluation
• Build automated testing around Data Science and ML code
• Work with engineering and platform teams on production integration while retaining model ownership
• Define and maintain offline evaluation frameworks
• Support online experimentation and measurement of recommendation effectiveness
• Monitor production behaviour and own model quality after launch
• Communicate technical information clearly to client stakeholders and the wider delivery team
• Build credibility with senior client Data Science stakeholders
• Operate independently within the client team
• Communicate progress, risks and technical decisions clearly
• Leave the recommendation capability more maintainable than it was found
• Travel according to project, client and organisational needs, estimated at 0%-15%