AI Platform Engineer 18054
Veritaz ABPublicerad: 2026-06-04
Ansök senast: 2026-07-04
Beskrivning
Veritaz is a leading IT staffing solutions provider in Sweden, committed to advancing individual careers and aiding employers in ensuring the perfect talent fit. With a proven track record of successful partnerships with top companies, we have rapidly grown our presence in the USA, Europe, and Sweden as a dependable and trusted resource within the IT industry.
Assignment Description
We are currently looking for an experienced AI Engineer with a strong focus on Generative AI to join a cross-functional team responsible for developing, deploying, and maintaining modern AI-powered solutions for both internal users and customer-facing services.
What You Will Work On
Language Models & Agentic AI
Design and develop AI applications powered by Large Language Models (LLMs)
Build Retrieval-Augmented Generation (RAG) solutions
Develop agent-based workflows and autonomous AI capabilities
Implement prompt engineering strategies and evaluation frameworks
Create intelligent systems capable of information retrieval, reasoning, and decision support
Improve user experiences through conversational and AI-driven interfaces
Integrate AI capabilities into internal and customer-facing platforms
Data Processing & Knowledge Management
Build scalable data ingestion and processing pipelines
Handle file uploads, content extraction, and information enrichment
Transform unstructured and semi-structured data into searchable knowledge assets
Design integrations with enterprise systems and external data sources
Store and manage data across object storage, vector databases, graph databases, and relational platforms
Ensure data quality, accessibility, and traceability throughout the data lifecycle
Operationalization & AI Platform Engineering
Deploy, monitor, and maintain AI services in production environments
Ensure scalability, reliability, security, and performance of AI applications
Manage AI platform lifecycle, monitoring, observability, and troubleshooting
Implement access control, security controls, and governance mechanisms
Optimize deployment pipelines and infrastructure automation
Support migration toward containerized and Kubernetes-based environments
Ensure compliance with financial industry security and data protection requirements
What You Bring
Strong experience developing AI and machine learning solutions in production environments
Hands-on experience with Generative AI, LLMs, and modern AI application architectures
Experience building Retrieval-Augmented Generation (RAG) solutions
Experience with prompt engineering and agent-based AI frameworks
Strong software engineering skills and understanding of full application lifecycles
Experience designing scalable backend services and APIs
Experience with cloud-native architectures and containerized environments
Strong understanding of security, observability, and operational excellence
Ability to collaborate effectively with technical and business stakeholders
Strong analytical and problem-solving capabilities
Experience working in agile and cross-functional teams
Assignment Description
We are currently looking for an experienced AI Engineer with a strong focus on Generative AI to join a cross-functional team responsible for developing, deploying, and maintaining modern AI-powered solutions for both internal users and customer-facing services.
What You Will Work On
Language Models & Agentic AI
Design and develop AI applications powered by Large Language Models (LLMs)
Build Retrieval-Augmented Generation (RAG) solutions
Develop agent-based workflows and autonomous AI capabilities
Implement prompt engineering strategies and evaluation frameworks
Create intelligent systems capable of information retrieval, reasoning, and decision support
Improve user experiences through conversational and AI-driven interfaces
Integrate AI capabilities into internal and customer-facing platforms
Data Processing & Knowledge Management
Build scalable data ingestion and processing pipelines
Handle file uploads, content extraction, and information enrichment
Transform unstructured and semi-structured data into searchable knowledge assets
Design integrations with enterprise systems and external data sources
Store and manage data across object storage, vector databases, graph databases, and relational platforms
Ensure data quality, accessibility, and traceability throughout the data lifecycle
Operationalization & AI Platform Engineering
Deploy, monitor, and maintain AI services in production environments
Ensure scalability, reliability, security, and performance of AI applications
Manage AI platform lifecycle, monitoring, observability, and troubleshooting
Implement access control, security controls, and governance mechanisms
Optimize deployment pipelines and infrastructure automation
Support migration toward containerized and Kubernetes-based environments
Ensure compliance with financial industry security and data protection requirements
What You Bring
Strong experience developing AI and machine learning solutions in production environments
Hands-on experience with Generative AI, LLMs, and modern AI application architectures
Experience building Retrieval-Augmented Generation (RAG) solutions
Experience with prompt engineering and agent-based AI frameworks
Strong software engineering skills and understanding of full application lifecycles
Experience designing scalable backend services and APIs
Experience with cloud-native architectures and containerized environments
Strong understanding of security, observability, and operational excellence
Ability to collaborate effectively with technical and business stakeholders
Strong analytical and problem-solving capabilities
Experience working in agile and cross-functional teams
