AI Solution Engineer

EPAM Systems; Göteborgs kommun; On-site; SEK 900,000 - 1,200,000; Full time

Benefits offered by this job

ESPP

Pension plan

Private healthcare insurance

Gym discounts

Wellness Grant

Learning & development opportunities

Job summary

EPAM Systems is seeking an experienced AI Solution Engineer to design, build, and operate advanced AI capabilities in Goteborg onsite. You will combine C#/.NET and Azure expertise with applied AI skills to clarify requirements, validate problems, and deliver measurable results.

You will work with stakeholders to turn requirements into buildable specifications, design AI services, and integrate models and APIs into production applications with robust testing and monitoring.

Qualifications

• Five years of professional software engineering experience, including two years building applied AI/ML solutions.
• Evidence of delivering at least one AI capability into production, with direct responsibility for implementation, deployment, evaluation and operational improvement.
• Strong hands-on C#, .NET and ASP.NET Core skills, including API design, asynchronous processing, automated testing, and integration with databases and enterprise systems.
• Practical Azure experience covering application hosting, identity, data access and AI services; solid DevOps foundation in CI/CD, containers and infrastructure automation.
• Working knowledge of ML and generative AI fundamentals, with hands-on experience integrating LLM APIs and retrieval-based applications.
• Ability to clarify ambiguous requirements, model data and workflow states and produce testable specifications; experience using AI coding assistants or agents with code review.
• Strong troubleshooting and communication skills to explain findings to technical and business colleagues.

Responsibilities

• Design and implement AI services and integrations using C#, .NET, ASP.NET Core and Azure, within architectural constraints.
• Integrate models, enterprise data, and APIs; implement retrieval-augmented generation and controlled agent workflows with human reviews.
• Build prototypes to test feasibility, then develop production-ready capabilities.
• Define evaluation datasets, quality thresholds, and confirm capability improvements with users.
• Implement CI/CD, automated testing, IaC, deployment, monitoring, and rollback; manage model and prompt versions.
• Address access control, sensitive data handling, prompt injection, and unpredictable outputs; document limitations and procedures.

Skills

C#

.NET

ASP.NET Core

API design

Azure

CI/CD

Automated testing

Database integration

DevOps

AI/ML fundamentals

Education

Bachelor's degree or equivalent

Tools

Kubernetes

Job description

AI Solution Engineers shape the future of business workflows by designing, building and operating advanced AI capabilities. In Goteborg, onsite collaboration with users, product teams, architects and delivery colleagues anchors technical innovation in practical outcomes. You combine C#/.NET and Azure expertise with applied AI skills to clarify requirements, validate problems and deliver reliable, measurable results. Leveraging precise specifications and AI coding agents, you support robust delivery and continuous improvement. This role matters because it connects technical excellence to real business impact.ResponsibilitiesWork with business stakeholders and users to understand workflows, clarify assumptions, assess data availability, and agree measurable acceptance criteria for AI capabilitiesTurn agreed requirements into buildable specifications covering inputs, outputs, data contracts, business rules, failure paths and validation scenariosDesign and implement AI services and integrations using C#, .NET, ASP.NET Core and Azure, making technical decisions within agreed architectural constraintsIntegrate models, enterprise data, and APIs into applications; implement retrieval-augmented generation and controlled agent workflows where appropriate, with clear human review and fallback pathsBuild focused prototypes to test feasibility and assumptions, then develop validated capabilities into maintainable production servicesUse AI coding agents against explicit specifications; review generated code, test behavior, diagnose failures and refine specifications or implementations based on evidenceDefine evaluation datasets and quality thresholds; validate output quality, security, latency and cost, and work with users to confirm the capability improves the intended workflowImplement CI/CD, automated testing, infrastructure as code, deployment, monitoring, and rollback; manage model and prompt versions and investigate production issuesAddress access control, sensitive data handling, prompt injection and unreliable outputs; document limitations, operating procedures and design decisionsExplain technical trade-offs and operating costs, surface risks early and provide implementation guidance and code reviews while keeping delivery within the agreed scopeRequirementsFive years of professional software engineering experience, including two years building applied AI/ML solutionsEvidence of delivering at least one AI capability into production, with direct responsibility for implementation, deployment, evaluation and operational improvementStrong hands-on C#, .NET and ASP.NET Core skills, including API design, asynchronous processing, automated testing, and integration with databases and enterprise systemsPractical Azure experience covering application hosting, identity, data access and AI services; a solid DevOps foundation in CI/CD, containers and infrastructure automationWorking knowledge of ML and generative AI fundamentals, with hands-on experience integrating LLM APIs and retrieval-based applications and evaluating their limitationsExperience defining evaluation criteria and representative test cases, monitoring AI behavior and balancing output quality, latency, reliability, and inference costAbility to clarify ambiguous requirements, model data and workflow states and produce testable specifications; practical experience using AI coding assistants or agents with code review and verificationStrong troubleshooting and communication skills: able to distinguish requirement gaps, data or model limitations, implementation defects and evaluation issues, and explain findings to technical and business colleaguesAbility to work independently within an agreed scope and collaborate across product, engineering and operationsRelevant degree or equivalent practical experienceNice to haveExperience with controlled agent workflows, tool integration, human approval mechanisms or business process automationPython, model adaptation or fine-tuning and established MLOps practices for custom modelsExperience with Kubernetes, reusable AI components or improving an existing enterprise codebaseAutomotive industry experience or relevant Azure, AI or cloud certificationsWe offerEPAM Employee Stock Purchase Plan (ESPP)Company’s pension planPrivate healthcare insuranceSafety & life insuranceGym discountsWellness Grant (SEK 2000)Corporate Programs including Employee Referral Program with rewardsLearning and development opportunities including in-house training and coaching, professional certifications, and courses