Role Overview

Do you have a strong AI engineering and intelligent automation background, passion for problem-solving, and want to join one of the largest tech companies in the Nordics? Then this is the role for you!

We are looking for an AI Engineer who wants to be part of Tieto Tech Consulting. Tieto Tech Consulting works as a true partner, solving clients’ toughest technology challenges and delivering reliable outcomes that drive measurable results. By merging data, cloud, AI and design with deep industry expertise, we create impactful yet intuitive digital solutions that empower people and move businesses forward.

Our team focuses on delivering enterprise-grade AI and automation solutions that improve operational efficiency, enhance knowledge accessibility, and streamline complex business workflows. We work closely with business, operations, and technology stakeholders to implement scalable AI-driven solutions in governed enterprise environments.

Responsibilities

When joining Tieto Tech Consulting as an AI Engineer:

You join a skilled team of AI engineers, automation specialists, cloud consultants, and data professionals where you learn new things with your colleagues
Architect and implement scalable AI solutions using Azure AI Search for enterprise retrieval, semantic search, and RAG-based applications
Design and automate business workflows using AI Builder and Power Automate, focusing on document intelligence, classification, routing, and exception handling
Develop Python services, utilities, and orchestration layers that integrate AI components with enterprise systems and APIs
Build and maintain agentic AI solutions using Claude Code, Claude agentic workflows, MCP, and sub-agent orchestration patterns
Leverage Snowflake Cortex for AI-assisted analytics, intelligent data processing, and conversational business insights
Apply data understanding techniques to structure, validate, and enrich structured and unstructured datasets for AI consumption
Partner with business and operations teams to identify opportunities for Lean Six Sigma-driven process improvement and automation
Define and enforce responsible AI, security, privacy, and governance controls across solution lifecycles
Create documentation, design artifacts, runbooks, and handoff materials suitable for enterprise support and audit readiness
Monitor solution performance, accuracy, adoption, and business impact through defined KPIs and continuous improvement practices

Requirements

Who we are looking for:

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience
3–5 years of hands-on experience in software engineering, AI engineering, data engineering, or intelligent automation
Strong proficiency in Python for API integration, workflow automation, and AI application development
Hands-on experience with Azure AI Search and enterprise search or retrieval-augmented generation implementations
Practical experience with AI Builder and Power Automate in enterprise environments
Familiarity with Claude Code, Claude agentic workflows, MCP, and multi-agent or sub-agent orchestration approaches
Experience with Snowflake Cortex or similar AI/LLM-enabled data platforms
Strong understanding of data profiling, data quality, metadata, taxonomy, and entity extraction
Demonstrated experience applying Lean Six Sigma or structured process improvement methodologies
Strong written and verbal communication skills with the ability to explain technical solutions to business stakeholders
You are fluent in English, both verbally and in writing

As a person, we believe you are a team player who takes action and demonstrates responsibility to organize your work and solve your tasks. With our agile end-to-end development process, you will continue to both learn from, and coach your colleagues, so communication is important for us. Technology is developing fast, so learning new innovative technologies is something you strive to do.

Additional Qualifications

We also believe you have:

Experience with Microsoft Power Platform, Dataverse, Azure services, and enterprise integration patterns
Exposure to MLOps, prompt evaluation, observability, and AI solution testing
Knowledge of governance frameworks, responsible AI, and model risk management
Experience in regulated or highly controlled enterprise environments
Lean Six Sigma certification, such as Green Belt or Black Belt
Experience building internal copilots, knowledge assistants, or operational automation platforms