Agentic AI & LLM Architecture – Agentic AI Solution Architect

Agentic AI & LLM Architecture – Agentic AI Solution Architect

Job Role: Agentic AI Solution Architect / AI Solution Architect

Primary Skill: Agentic AI & LLM Architecture

Skill Level: Any

Location: All Romania

Language: English 

Role Overview

We are looking for an experienced Agentic AI Solution Architect responsible for designing, governing, and enabling enterprise-scale Agentic AI and LLM-based solutions.

The role will define AI architecture standards and ensure that AI platforms and solutions are scalable, secure, performant, cost-efficient, and production-ready, while remaining aligned with business objectives.

The architect will work closely with AI Engineers, business stakeholders, technology teams, and other architects to transform new business opportunities and AI use cases into viable technical solutions. The role will also contribute to proposals, solution estimates, technical feasibility assessments, and effort estimation.

Key Responsibilities

AI Architecture & Solution Design

• Define end-to-end architectures for enterprise-scale Agentic AI and LLM-based solutions.
• Design scalable architectures covering AI applications, models, data, integration, orchestration, security, and infrastructure.
• Define architecture standards, patterns, principles, and governance for Agentic AI solutions.
• Assess new AI use cases and translate business requirements into technically viable solutions.
• Evaluate architectural options and recommend appropriate technologies, platforms, and implementation approaches.
• Ensure solutions are designed for production readiness and enterprise adoption.

Agentic AI & LLM Architecture

• Design agent orchestration architectures for multi-agent and autonomous AI solutions.
• Design and govern Retrieval-Augmented Generation (RAG) architectures.
• Define LLM integration patterns, model selection approaches, prompt engineering strategies, and AI service architectures.
• Design AI platforms supporting agents, tools, knowledge sources, APIs, workflows, and enterprise applications.
• Define appropriate approaches for context management, memory, grounding, evaluation, and observability.
• Address scalability, latency, reliability, and model performance requirements.

Cloud & Enterprise Architecture

• Design AI solutions using cloud platforms, preferably Microsoft Azure.
• Define secure and scalable cloud architectures for AI/ML workloads.
• Ensure appropriate integration with enterprise applications, APIs, data platforms, and identity services.
• Design architectures that optimise performance, scalability, availability, and cloud costs.
• Ensure alignment with enterprise architecture and technology standards.

Security & Governance

• Ensure Agentic AI solutions meet enterprise security and governance requirements.
• Incorporate security and privacy considerations into AI architecture and solution design.
• Define appropriate controls for access, identity, data protection, model usage, and AI agents.
• Address risks associated with LLMs and Agentic AI, including data exposure, inappropriate tool usage, hallucinations, and uncontrolled agent behaviour.
• Establish architectural guardrails for responsible and secure AI adoption.

Technical Leadership

• Provide technical leadership to AI Engineers and development teams.
• Review and guide implementation approaches and architectural decisions.
• Mentor technical teams on AI architecture, LLM integration, Agentic AI patterns, and cloud implementation.
• Facilitate technical design discussions and architecture reviews.
• Ensure engineering solutions remain aligned with the defined target architecture.

Business & Stakeholder Engagement

• Collaborate with business and technology stakeholders to understand objectives, constraints, and expected outcomes.
• Participate in discovery workshops for new AI opportunities and use cases.
• Translate business needs into technical architectures and implementation roadmaps.
• Communicate complex AI architecture concepts clearly to both technical and non-technical stakeholders.
• Balance business value, technical feasibility, risk, complexity, and cost.

Presales & Solution Proposals

• Support new AI use cases and proposals with technical solution designs.
• Assess the technical feasibility and complexity of proposed Agentic AI solutions.
• Define high-level solution architectures, technology choices, dependencies, and implementation approaches.
• Provide effort estimates and delivery assumptions for proposed solutions.
• Identify technical risks, constraints, dependencies, and required skills/resources.
• Contribute to presentations, solution proposals, PoCs, and customer-facing technical discussions.

Required Skills & Experience

Experience

• 10+ years of overall professional experience in software, technology, AI/ML, architecture, or related disciplines.
• Strong background in AI/ML architecture and enterprise solution design.
• Proven experience designing complex AI/ML or cloud-based solutions.
• Experience taking AI solutions from conceptual design through to production architecture.

Agentic AI & LLM

• Strong understanding of LLMs and Generative AI.
• Practical experience with Agentic AI architectures.
• Experience designing:
• • Agent orchestration
  • Multi-agent solutions
  • RAG architectures
  • LLM-based applications
  • AI platforms
  • AI-powered workflows
• Understanding of LLM integration, prompt engineering, grounding, evaluation, and AI application patterns.

Python

• Strong Python programming and code-review skills.
• Ability to understand, design, review, and guide production-quality Python-based AI solutions.
• Experience with Python AI/ML and/or LLM frameworks is highly desirable.

Cloud

• Strong experience with cloud platforms, with Microsoft Azure preferred.
• Ability to design scalable, secure, and cost-efficient cloud architectures.
• Understanding of cloud-native services, APIs, containers, security, networking, monitoring, and infrastructure relevant to AI platforms.

Solution Design & Estimation

• Strong solution architecture and technical design skills.
• Ability to assess new business use cases and propose appropriate AI/technology solutions.
• Experience producing high-level technical solutions and effort estimates.
• Ability to break complex AI initiatives into components, dependencies, implementation phases, and delivery estimates.

Stakeholder Management

• Strong communication and stakeholder management skills.
• Ability to communicate architecture decisions and trade-offs to senior business and technology stakeholders.
• Experience working across multidisciplinary and distributed teams.
• Strong consulting and problem-solving mindset.

Nice to Have

• Experience with Microsoft Azure AI services / Azure OpenAI.
• Experience with AI agent frameworks and orchestration technologies.
• Knowledge of vector databases and enterprise search.
• Experience with AI observability, evaluation, and monitoring.
• Knowledge of MLOps / LLMOps.
• Experience with Kubernetes and containerised AI workloads.
• Experience with API management and event-driven architectures.
• Knowledge of DevSecOps and infrastructure-as-code.
• Experience designing responsible AI and AI governance frameworks.
• Experience with enterprise data platforms and data governance.
• Experience delivering AI Proofs of Concept and converting them into production solutions.
• Presales / consulting experience supporting proposals and customer engagements.

Technical Environment

• Agentic AI
• LLMs / Generative AI
• RAG / Retrieval-Augmented Generation
• Agent Orchestration / Multi-Agent Architectures
• Python
• Microsoft Azure
• Azure OpenAI / Azure AI Services
• APIs & Enterprise Integration
• Vector Databases / Enterprise Search
• Cloud-Native Architecture
• AI Security & Governance
• AI Observability / Evaluation
• MLOps / LLMOps
• DevSecOps

Key Competencies

• Agentic AI architecture
• LLM solution architecture
• AI/ML architecture
• RAG architecture
• Agent orchestration
• Enterprise cloud architecture
• Python
• AI platform design
• Security and governance
• Scalability and performance
• Cost optimisation
• Technical leadership
• Solution design
• Business-to-technology translation
• Presales / proposal support
• Effort estimation
• Stakeholder management

Seniority Expectations

Skill Level: Any

Although the requested classification is Any, the role itself requires senior/architect-level capabilities, particularly given the 10+ years' experience requirement and responsibility for enterprise AI architecture.

The successful candidate should be able to:

• Independently define end-to-end architectures for complex Agentic AI and LLM solutions.
• Act as the technical authority for AI architecture decisions.
• Evaluate and architect new AI use cases from business requirements through production design.
• Guide AI Engineers and development teams.
• Make informed architectural trade-offs covering security, scalability, performance, reliability, and cost.
• Lead technical discussions with senior business and technology stakeholders.
• Produce technical solutions and effort estimates for new proposals and use cases.
• Establish reusable architecture patterns and standards for enterprise AI adoption.

Position Summary