Oferta wygasa za:89 dni
Tryb pracyZdalna
Rodzaj umowyKontrakt B2B
Tryb rekrutacjiRekrutacja stacjonarna
BranżaIT
About the project
We are looking for an experienced Enterprise AI Architect to lead the design and development of enterprise-grade AI solutions for a large-scale business transformation initiative.
The role combines enterprise architecture, hands-on AI engineering, technical leadership, and client-facing consulting. You will be responsible for defining the technical architecture, designing scalable and reusable AI capabilities, and ensuring their successful implementation in real business environments.
You will work directly with senior business stakeholders, technical leadership, and domain experts to identify opportunities for AI adoption, translate business challenges into technical solutions, and drive projects from initial concept and presales through implementation and continuous improvement.
This is a highly technical, hands-on role requiring extensive experience in AI engineering and software architecture, as well as the ability to communicate complex technical concepts to non-technical stakeholders.
You will also provide technical leadership to a team of engineers, establish engineering standards, and make strategic decisions regarding AI platforms, tools, and integration approaches.
Your responsibilities
- Define and own the overall technical architecture of enterprise AI solutions, including shared components, reusable capabilities, integration patterns, and deployment strategies.
- Establish architectural standards and best practices for AI solution development, including versioning, testing, evaluation, and release management.
- Make and justify platform-level technology decisions, including AI frameworks, agent orchestration platforms, integration architectures, and build-versus-buy strategies.
- Define architectural principles and quality standards for reusable AI components and ensure compliance through technical reviews.
- Provide technical leadership and guidance to a team of engineers, including code reviews, architectural decisions, and technical problem-solving.
- Ensure solutions meet enterprise requirements related to scalability, reliability, security, data protection, and compliance.
- Design, build, test, and maintain production-ready AI solutions and reusable AI capabilities.
- Remain hands-on throughout the development lifecycle, writing and reviewing code and contributing directly to implementation.
- Develop AI-powered workflows and agentic solutions using modern LLM technologies, orchestration frameworks, and tool integration patterns.
- Design evaluation frameworks, including test datasets, acceptance criteria, regression testing, and quality assurance processes for non-deterministic AI systems.
- Investigate and resolve issues related to AI agent behaviour, workflow execution, and output quality.
- Integrate AI solutions with enterprise platforms, business applications, and data sources.
- Ensure that AI solutions are reliable, maintainable, and suitable for production use.
- Work directly with senior client stakeholders, including CTOs, enterprise architects, and business leaders, to identify business needs and define technical solutions.
- Assess business processes to determine where AI can deliver measurable value and where traditional software solutions are more appropriate.
- Lead technical discovery sessions and translate ambiguous business requirements into clear architectural designs and implementation plans.
- Shape solution proposals, define project scope, estimate implementation effort, and present technical approaches to clients.
- Communicate architectural decisions, technical trade-offs, and business benefits to both technical and non-technical audiences.
- Participate actively in presales activities, supporting the development and presentation of AI solution proposals.
- Take ownership of business outcomes, focusing on user adoption, operational efficiency, and measurable improvements.
- Monitor developments in AI technologies, tools, and platforms and assess their applicability to enterprise use cases.
- Identify opportunities to introduce new AI capabilities and improve existing solutions.
- Lead pilot implementations, gather feedback from end users, and drive iterative improvements.
- Establish standards for developing, reviewing, versioning, and releasing reusable AI components.
- Promote engineering excellence and continuous improvement across the AI development lifecycle.
Our requirements
- Extensive experience in enterprise software architecture, AI solution architecture, or a similar senior technical leadership role.
- Proven track record of designing and owning complex, production-grade software systems, including architecture, integrations, reusable components, and non-functional requirements.
- Strong software engineering background and the ability to actively design, develop, test, review, and maintain production-quality code.
- Experience with modern software engineering practices, including version control, code reviews, automated testing, and CI/CD.
- Strong technical foundation in at least one modern programming ecosystem, such as TypeScript/Node.js, Python, Java, or .NET.
- Experience designing scalable, maintainable, and reusable software architectures.
- Knowledge of TypeScript and Node.js is an advantage but is not mandatory.
- Extensive hands-on experience with modern AI technologies, platforms, and tools, with a broad understanding of the current AI ecosystem.
- Proven experience designing, building, and deploying LLM-powered solutions used in real production environments.
- Strong understanding of agentic AI architectures and patterns, including:
- AI agents and tool use/function calling.
- Model Context Protocol (MCP).
- Prompt engineering and context engineering.
- Structured instruction design.
- Agent orchestration and workflow automation.
- Experience evaluating, selecting, and integrating AI platforms and tools based on specific business and technical requirements.
- Practical experience building evaluation frameworks for AI systems, including test cases, measurable acceptance criteria, and regression testing.
- Ability to troubleshoot AI-powered workflows and systematically improve the reliability and quality of non-deterministic outputs.
- Strong understanding of when AI is appropriate and when conventional software engineering is a more suitable solution.
- Experience defining architecture standards, reusable components, and engineering practices across multiple projects or teams.
- Ability to make strategic technology decisions and evaluate the trade-offs between different platforms and architectural approaches.
- Understanding of enterprise security, data protection, and compliance requirements.
- Experience working with sensitive business data is highly desirable.
- Proven experience working directly with external clients, senior executives, and business stakeholders.
- Strong consulting and presales background, including solution design, project scoping, effort estimation, and presenting technical proposals.
- Ability to translate complex and ambiguous business requirements into clear technical architectures and executable implementation plans.
- Excellent communication and presentation skills, with the ability to explain complex technical concepts to non-technical audiences.
- A product-oriented mindset, focusing on business value, user adoption, and measurable outcomes rather than technology alone.
- Ability to work independently in environments with evolving requirements and limited initial specifications.
- Proven experience providing technical leadership to engineering teams, including architectural guidance, code reviews, and technical decision-making.
- Ability to influence technical direction and establish engineering standards.
- Excellent problem-solving and decision-making skills.
- English proficiency at C1 level or higher, with the ability to independently lead technical and business discussions with international clients.
- Availability to work in alignment with the client's business hours in the US and Western Europe.
- Willingness to remain actively involved in software development rather than focusing exclusively on management or documentation.
- Seniority: Enterprise Architect / Principal-level AI Engineer.
- Role type: Hands-on technical leadership.
- Key focus: Enterprise AI architecture, AI engineering, technical consulting, and presales.
- Working model: Availability aligned with US and Western European business hours.
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