Apprecode

We're looking for a Senior Azure Platform / AI Engineer for a long-term engagement with an enterprise client. You'll work directly with the client's IT and Security teams in a sprint-based model. 

What you'll do:

• Design and maintain Azure infrastructure: AKS, Entra ID, Private Endpoints, VNets, Network Security Perimeters, multi-region
• Deploy and operate AI/ML workloads: Azure OpenAI, AI Foundry, RAG, multi-agent systems, vLLM, embedding pipelines
• Own IaC & CI/CD: Terraform, GitHub Actions, OIDC federation, Helm/Kustomize, secret management
• Data integrations: Microsoft Fabric, PostgreSQL, Python ETL, Power BI API
• Backend/frontend support: Python/FastAPI (async), React + TypeScript (Vite)

Stack:
Azure AKS Entra ID RBAC Key Vault APIM AI Search Azure OpenAI AI Foundry Azure ML Terraform GitHub Actions Helm Microsoft Fabric PostgreSQL FastAPI React TypeScript

Requirements:

• 5+ years of Azure platform engineering
• Strong communication with enterprise clients (English)
• Experience working with IT/Security stakeholders

Nice to have:

• Production AKS & Azure ML model serving
• Azure OpenAI in production
• Locked-down / regulated Azure tenants
• FDE or embedded team experience

Format: Remote, Europe, long-term , sprint model, start ASAP.

We’re hiring an experienced Senior Python Backend Engineer / Technical Lead for a long‑term engagement. This is a full‑time contract role available only to candidates legally resident in the European Union.

Important: the contractor will receive company equipment. During onboarding we will verify identity and EU residency — only candidates able to provide valid documentation will be considered.

What you’ll do

• Develop and maintain production‑grade backend systems using Python.
• Design service architecture for high‑throughput, parallel processing, and reliability‑sensitive systems.
• Build microservices, REST APIs, backend integrations, and data‑processing components.
• Make technical decisions on scalability, fault tolerance, application security, and performance.
• Own assigned functionality end‑to‑end: technical design, estimation, implementation, testing, and release.
• Collaborate closely with Product, Architecture, QA, Infrastructure, and DevOps teams.
• Maintain engineering quality through code reviews, automated tests, and CI/CD practices.
• Mentor less experienced engineers and contribute to shared backend architecture and development standards.

Must‑have

• 6+ years of commercial software development experience with Python as a primary technology.
• Deep Python knowledge: OOP, asynchronous programming, design patterns, concurrency, and performance optimization.
• Proven experience designing and building distributed backend systems and microservice architectures.
• Strong hands‑on experience with at least one Python web framework: FastAPI, Flask, or Django.
• Solid track record building and maintaining RESTful APIs.
• Practical understanding of high‑load architecture, scalability, resiliency, and secure software development.
• Strong database skills (PostgreSQL or SQL Server) and experience with NoSQL solutions.
• Production experience with Docker and Kubernetes.
• Hands‑on experience with Microsoft Azure, Azure DevOps, and automated CI/CD pipelines.
• Ability to independently drive technically complex tasks and make sound architectural decisions.
• Experience working in Agile teams.
• Strong communication, code review, and mentoring skills.
• Degree in Computer Science, Software Engineering, or a related technical field.

Nice‑to‑have

• Commercial experience with Generative AI or LLM‑based products.
• Familiarity with RAG architectures, AI agents, or agentic workflows.
• Experience integrating AI capabilities or workflow automation into backend platforms.

📍 EU Only | 🕐 Full‑Time | 📅 12+ Months

About the role:
We're looking for an experienced engineer to design and build enterprise knowledge graphs and semantic data layers. You'll work at the intersection of data architecture, AI, and business domains — formalizing business knowledge into machine-readable models.

Responsibilities:

• Design, develop, and implement enterprise-grade knowledge graphs
• Build semantic layers that establish shared business understanding across enterprise systems
• Model business entities, relationships, taxonomies, ontologies, and controlled vocabularies
• Create semantic data products for AI applications, analytics platforms, and business users
• Design enterprise metadata models and integrate them with data catalogues
• Connect structured and unstructured enterprise data within a unified semantic model
• Maintain governance, lineage, metadata quality, and semantic consistency

Requirements:

• Hands-on experience designing and implementing knowledge graphs
• Semantic technologies: RDF, OWL, SKOS, SPARQL
• Graph databases: Neo4j, Amazon Neptune, Stardog, GraphDB, or equivalent
• Enterprise metadata management & data catalogue platforms
• Experience developing ontologies, taxonomies, and controlled vocabularies
• Strong enterprise data architecture and data modelling knowledge
• Advanced SQL and multi-system data integration
• Cloud platforms: Azure, AWS, or GCP

Nice to have:

• Semantic or enterprise search solutions
• Master Data Management (MDM)
• Data Mesh / Data Product concepts
• Enterprise data governance frameworks
• AI agents, GenAI, or RAG architectures

About the Role

We're looking for a seasoned engineer who bridges deep cloud infrastructure expertise with a security-first mindset. Your goal is to embed security into every stage of the development lifecycle — not bolt it on at the end.

What You'll Be Doing:

• Architect and maintain fault-tolerant infrastructure across AWS and Azure using Terraform, with a focus on modular design and immutable infrastructure principles
• Implement automated IaC policy checks (Checkov, Tfsec, OPA/Rego) to surface misconfigurations as early as the code review stage
• Build and harden end-to-end CI/CD pipelines (GitHub Actions, Azure DevOps, GitLab CI) with integrated SAST/DAST, container scanning, secret detection, and software composition analysis
• Apply zero-trust principles through a well-structured IAM strategy, RBAC, and centralized secrets management (HashiCorp Vault, Azure Key Vault)
• Deploy and secure containerized workloads on Kubernetes clusters (EKS / AKS)
• Automate the baking of EDR agents, vulnerability scanners, and observability tooling into golden base images (AMIs, Azure Golden Images)
• Continuously audit cloud posture via AWS Security Hub and Azure Defender, maintaining alignment with SOC2, ISO 27001, and CIS Benchmarks
• Build automated workflows that collect security findings, score them by risk, and route them into engineering backlogs (Jira)
• Centralize application, container, and infrastructure log delivery into SIEM systems to enable real-time threat detection
• Act as a bridge between Security and Engineering — delivering developer-friendly remediation guidance and maintaining reusable secure-by-default templates (Terraform modules, Helm charts)

What We're Looking For:

• 3+ years in Cloud Operations, DevOps, or DevSecOps with hands-on production experience across both AWS and Azure
• Proven track record of building and securing CI/CD pipelines at scale
• Strong proficiency with Terraform (modular architecture), and familiarity with Bicep or CloudFormation
• Scripting skills in Python, Bash, or PowerShell
• Solid understanding of Docker and Kubernetes (EKS/AKS): security hardening, service mesh, and container runtime defense
• Hands-on experience with security tooling such as SonarQube, Prisma Cloud, Wiz, Snyk, CrowdStrike, Microsoft Sentinel, or equivalents
• Practical knowledge of cloud network security, encryption, and end-to-end vulnerability management

Nice-to-Have Certifications:

• Certified DevSecOps Professional (CDP) or Practical DevSecOps
• AWS Certified Security – Specialty / Azure Security Engineer Associate
• CKA or CKS (Kubernetes)