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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and deploying intelligent automation solutions within the Microsoft Azure ecosystem, with a strong focus on Python development, AI integration, and responsible AI practices. Capable of translating complex business problems into scalable AI solutions while ensuring adherence to best practices in software development and model governance.
Highest-signal resume keywords
Python DevelopmentMicrosoft Azure EcosystemAI Solution DeliveryAPIs and MicroservicesModel Governance
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Design, build, and deploy intelligent automation solutions using the Microsoft Azure ecosystem
- Develop and maintain production-grade Python services integrated with AI models, Azure AI Foundry workflows, APIs, datasets, and enterprise systems
- Create reusable AI components, frameworks, and engineering patterns for multiple teams and business functions
- Define and champion best practices for prompt engineering, model governance, AI evaluation, security, and responsible AI deployment
- Contribute to AI architecture discussions, technical design decisions, performance optimization, and engineering standards
- Deliver end-to-end AI-powered automation for high-volume, repetitive processes across Payroll, Products, and other internal functions
- Build intelligent document processing, NLP workflows, AI assistants, agentic automation, RAG, RAA, knowledge management, and enterprise search solutions
- Develop secure integrations between AI services and enterprise applications using APIs, microservices, and Python-based automation
- Build and maintain data ingestion, transformation, embeddings, vector indexing, retrieval, monitoring, and evaluation pipelines
- Partner with Payroll, Product, and Business SMEs to identify automation opportunities and deliver measurable business outcomes
- Translate business problems into scalable AI solution designs and technical requirements
- Communicate AI capabilities, limitations, risks, and value to technical and non-technical stakeholders
- Collaborate with Smart Automation engineers to ensure consistent architecture, engineering quality, and reusable design patterns
- Ensure version control, testing, observability, monitoring, and secure software development practices
- Participate in incident reviews and continuously improve AI architectures
- Promote model evaluation, telemetry, traceability, prompt management, and responsible AI practices
- Stay current with Azure AI and Generative AI capabilities and identify safe adoption opportunities
- Raise risks, dependencies, and blockers early to maintain sprint commitments
Requirements
What you’ll need- Degree in Computer Science, Software Engineering, Data Science or a related technical discipline
- Minimum 5 years of hands-on Python development experience in production environments, including backend development, APIs, automation, integrations, testing, and software engineering best practices
- Minimum 3 years of hands-on experience within the Microsoft Azure ecosystem
- Minimum 3 years of experience delivering AI or Machine Learning solutions in production or enterprise environments
- Experience with Azure AI Foundry, Azure OpenAI, Azure AI Search, model orchestration, vector search, secure prompt pipelines, and evaluation frameworks
- Experience developing production-grade Python services integrated with AI models, Azure AI Foundry workflows, AI hubs, datasets, APIs, and enterprise systems
- Knowledge of intelligent document processing, document understanding, NLP workflows, AI assistants, agentic automation, RAG, RAA, knowledge management, and enterprise search
- Experience with APIs, microservices, data ingestion, transformation, embeddings generation, vector indexing, retrieval, monitoring, and evaluation
- Understanding of version control, testing, observability, monitoring, secure software development, model governance, AI evaluation, security, and responsible AI deployment
- Feature branches and peer-reviewed pull requests
- Unit tests developed alongside code
- Azure Key Vault for secrets and credentials
- Managed Identity and Zero Trust principles
- Content Safety controls, grounding mechanisms, evaluation frameworks, and Responsible AI guardrails before deployment
- Ability to collaborate with Payroll and Product SMEs and communicate AI capabilities, limitations, risks, and confidence levels transparently
Benefits
Comp & perks- Comprehensive training and development programs
- Flexible working schedule
- Private medical insurance 100% covered by SD Worx
- 25 vacation days
- 18 hours for personal matters
- Reduced summer hours: 36 hours instead of 40 per week, for 4 weeks (to be chosen in July or August)
- Edenred flexible retribution options: meal vouchers, transport vouchers, etc.
- Laptop and equipment provided
- Workation: possibility to work from any SD Worx location (4 weeks per year, EU only)
- Learning opportunities: individual training bonus, an individual development plan, and professional training
- Career growth opportunities
- Individual training bonus
- Professional training
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonAI ModelsAzure AI FoundryNLP WorkflowsData IngestionVector IndexingSecure Software DevelopmentTesting and ObservabilityAutomationMachine Learning
Soft Skills
CollaborationCommunicationProblem-SolvingStakeholder EngagementTransparency
Tools & Technologies
Azure OpenAIAzure AI SearchAzure Key VaultManaged IdentityZero Trust Principles
Industry Keywords
Intelligent AutomationResponsible AIModel EvaluationDocument ProcessingEnterprise Systems