AI Architect - Agentic AI & Enterprise Platforms

EPAM Systems; Göteborgs kommun; On-site; SEK 1,200,000 - 1,600,000; Full time

Benefits offered by this job

ESPP

Pension plan

Private healthcare insurance

Gym discounts

Wellness grant

Employee referral program

Learning and development opportunities

Job summary

EPAM Systems seeks an AI Architect focused on agentic AI and enterprise platforms in Goteborg. You will own architecture for defined solutions, collaborating onsite with client enterprise architects and specialists in security, identity, data and integration.

You translate business needs into practical architectures, guide delivery from design to production adoption, and help clients realize value through robust, scalable platforms.

Qualifications

• Seven years of experience in software engineering, cloud platforms, data/AI engineering or solution architecture.
• Two years owning architecture or leading technical design.
• Two years designing or delivering AI solutions, including recent hands-on work with LLM-based applications.
• Architecture ownership of at least one LLM-based solution deployed to production, with evaluation results and lessons.
• Experience with model selection, retrieval-augmented generation (RAG) and agent orchestration.
• Knowledge of enterprise AI platforms, APIs, and secure integration patterns.
• Proficiency in Python or another language for prototypes and investigation.
• Ability to document decisions, run workshops, and explain trade-offs to stakeholders.
• Ability to structure ambiguous requirements and coordinate across teams and vendors.

Responsibilities

• Translate business use cases into architecture requirements and an actionable roadmap.
• Develop target architectures, integration designs, and reusable patterns for AI solutions.
• Evaluate models, agent frameworks, and platforms against quality, security, and cost criteria.
• Collaborate on identity, data access and interoperability across vendor platforms.
• Build prototypes, review designs, and help engineers move to production.
• Define evaluation criteria, observability and operational controls with security teams.
• Facilitate architecture workshops and document decisions and trade-offs.

Skills

Python

Cloud platforms

AI engineering

Architecture

LLM-based apps

Prototyping

Documentation

Stakeholder communication

Tools

APIs

Identity & access control

Job description

As an AI Architect focused on agentic AI and enterprise platforms, you shape how organizations design and implement advanced AI solutions. In Goteborg, you independently own architecture for defined solutions or platform workstreams, collaborating onsite with client enterprise architects and specialists in security, identity, data and integration. You translate business needs into practical architectures, evaluate technology choices, and guide delivery from initial design through production adoption. This role matters because it enables enterprise clients to realize the value of agentic AI through robust, scalable and secure platforms.ResponsibilitiesTranslate business use cases and constraints into architecture requirements, measurable success criteria and an achievable implementation roadmapDevelop target architectures, integration designs, and reusable patterns for AI solutions and platform capabilities, aligned with enterprise standardsEvaluate models, agent frameworks, orchestration approaches, and enterprise platforms against quality, security, interoperability, reliability, latency and cost requirementsCollaborate with domain specialists to address identity, authorization, data access, tool integration and interoperability across vendor platforms and existing systemsBuild focused prototypes or reference implementations, review technical designs and help engineers resolve architectural issues as solutions move into productionDefine evaluation criteria, observability, human oversight, failure handling and operational controls with engineering, security and responsible-AI teamsFacilitate architecture workshops, reconcile input from client teams and vendors and document decisions, trade-offs, dependencies and implementation guidanceGuide teams in applying agreed patterns and standards, mentor engineers on architecture and use delivery feedback to improve the designTranslate relevant developments in agentic AI into practical recommendations grounded in client needs and implementation evidenceRequirementsSeven years of experience in software engineering, cloud platforms, data/AI engineering or solution architecture, including two years owning architecture or leading technical designTwo years designing or delivering AI solutions, including recent hands-on work with LLM-based applicationsArchitecture or technical design ownership of at least one LLM-based solution deployed to production, with the ability to explain integration choices, evaluation results and operational lessonsPractical experience with model selection, retrieval-augmented generation (RAG), tool use and agent orchestration, including the judgment to choose between agentic workflows and simpler approachesExperience designing solutions in a complex enterprise environment; strong knowledge of at least one cloud or enterprise AI platform, APIs, integration patterns, identity and access controlProficiency in Python or another relevant language sufficient to build prototypes, review implementation choices and investigate integration issuesPractical understanding of evaluation, deployment, monitoring and cost management, together with data protection, prompt-injection risks, tool permissions and human oversightAbility to produce clear diagrams, decision records and implementation guidance; facilitate client workshops; and explain technical trade-offs to engineers and business stakeholdersAbility to structure ambiguous requirements, work across teams and vendors and build agreement without formal authority, while escalating decisions beyond the workstream's scopeNice to haveExperience with multiple enterprise AI platforms, shared agent services or centralized capabilities for agent registration, policy enforcement, and monitoringFamiliarity with Model Context Protocol (MCP), agent-to-agent interoperability, tool gateways, execution sandboxing, agent identity or knowledge graphsExperience turning architecture patterns into adopted standards across teams in a large or federated enterpriseFamiliarity with responsible-AI governance and the EU AI Act, and experience working with legal, risk or compliance specialistsExperience in automotive, manufacturing or similarly complex enterprise environmentsWe 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