Senior AI

Salt; Amsterdam; Hybrid; EUR 90,000 - 130,000; Full time

Job summary

Salt is seeking a Senior AI Engineer / AI Solutions Architect to lead the design and implementation of agentic AI solutions in Amsterdam, with hybrid work options. The role focuses on architecting scalable AI-powered applications, integrating with enterprise systems and delivering production-ready software.

The candidate will build multi-agent workflows, establish evaluation frameworks and governance, and collaborate with product and technology stakeholders to define the technical roadmap.

Qualifications

• 5+ years of software engineering or related field.
• Hands-on in GenAI production apps and agentic workflows.
• Experience with leading LLM platforms (OpenAI, Claude).
• Ability to design scalable, secure, production-ready AI solutions.
• Proven experience integrating with enterprise systems via APIs.

Responsibilities

• Architect and develop AI-powered applications, agents and multi-agent workflows.
• Design scalable solutions using shared services and existing platforms.
• Translate business requirements into technical designs and prototypes.
• Develop reusable frameworks and patterns across AI use cases.
• Ensure security, reliability, maintainability and production readiness.

Skills

Software architecture

GenAI applications

Agentic workflows

LLM platforms

APIs & enterprise integration

Security & governance

CI/CD & production ops

Testing & reliability

Multi-agent systems

Memory management

Observability & monitoring

Tools

OpenAI/ChatGPT

Anthropic Claude

Claude Code / Codex

Jira

Confluence

Job description

Senior AI Engineer / AI Solutions Architect (Agentic AI) – Amsterdam/Hybrid

Duration: 6 months

Start: ASAP

We are looking for an experienced Senior AI Engineer to help architect, build and scale a new generation of AI-powered products and agentic solutions.

The organisation has already developed several AI use cases and early-stage solutions. The next phase is to evolve these into a coherent, scalable product ecosystem by identifying reusable capabilities, shared services and common architectural patterns that can support multiple business workflows.

This role is ideal for a strong Software Engineer and Solution Architect with hands-on experience building GenAI applications, AI agents and multi-agent systems. The focus is on applying existing AI technologies to solve real business problems, integrating with enterprise systems and delivering secure, production-ready solutions.

Key Responsibilities

• Architect and develop AI-powered applications, agents and multi-agent workflows.
• Design scalable solutions that leverage shared services, enterprise knowledge and existing platforms.
• Translate business requirements into technical designs, prototypes and production-ready applications.
• Build reusable frameworks, components and patterns across multiple AI use cases.
• Design and implement:
• Agent orchestration
• Retrieval and grounding strategies
• Context and state management
• Tool calling and MCP integrations
• Integrate AI solutions with enterprise systems and knowledge sources via APIs.
• Implement evaluation frameworks, observability, guardrails and governance controls.
• Ensure solutions meet engineering standards for security, reliability, maintainability and scalability.
• Rapidly prototype new ideas and technologies while maintaining a clear path to production.
• Collaborate closely with product, business and technology stakeholders to define technical direction and roadmap.

Required Skills & Experience

• 5+ years' experience in Software Engineering, Backend, Full Stack, Platform Engineering or similar.
• Strong software architecture and system design expertise.
• Hands-on experience building Generative AI applications in production environments.
• Practical experience developing AI agents and agentic workflows.
• Experience with leading LLM platforms including:
• OpenAI / ChatGPT
• Anthropic Claude
• Experience with:
• MCP and tool integrations
• APIs and enterprise integrations
• RAG and retrieval architectures
• Context engineering and memory management
• AI evaluation frameworks
• Observability and monitoring
• AI guardrails and governance
• Excellent software engineering fundamentals including:
• Testing
• Security
• CI/CD
• Monitoring
• Production operations
• Demonstrated experience taking AI solutions from PoC to production.
• Multi-agent architectures and agent-as-tool design patterns.
• AI-assisted development tools such as Claude Code, Codex or similar.
• Enterprise productivity platforms including Jira, Confluence, Google Workspace and Slack.
• Project, Programme or Business Operations workflows.
• AI solutions capable of taking actions in enterprise systems with appropriate controls and approvals.
• Experience working within large-scale, regulated or privacy-sensitive environments.