Senior AI Engineer

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Valtech

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1997

🤝 B2B

☁️ SaaS

B2B • Marketing • SaaS

Valtech is a global digital agency focusing on experience innovation. They strive to transform businesses through a combination of technology, marketing, and data strategies. Valtech helps companies elevate their digital presence and drive commerce strategies, enhance enterprise digital transformations, and unlock marketing and performance potential. They also utilize data and AI to help organizations harness the power of information. With offices around the world, Valtech partners with businesses to shape their digital futures, offering a range of services and insights designed to enhance customer experiences.

📋 Description

• Drive complex AI engineering workstreams across multiple business areas, use cases, products, or stakeholder groups. • Define AI engineering approaches that align business goals, workflow opportunities, orchestration patterns, integration requirements, and measurable implementation outcomes. • Translate ambiguous stakeholder needs into structured implementation plans, workflow logic, prompt orchestration, retrieval patterns, tool-calling approaches, and solution recommendations. • Guide the implementation of AI-enabled applications, agents, assistant-style experiences, and workflow components that connect models to practical business processes. • Establish and reinforce best practices for prompt orchestration, tool use, context handling, retrieval flow, API integration, workflow composition, response processing, testing, and code quality. • Design and improve reusable implementation patterns for use cases such as summarization, extraction, question answering, search augmentation, conversational support, workflow automation, grounded insight delivery, and agent-assisted task execution. • Contribute to delivery planning, prioritization discussions, and quality standards across AI engineering engagements. • Mentor, coach, and support practitioners through feedback, guidance, and performance development. • Review deliverables for clarity, technical rigor, quality, consistency, safety, and business usefulness. • Help teams improve workflow reliability, integration quality, testing discipline, and implementation reuse across projects. • Collaborate with AI Scientists, Data Scientists, Data Engineers, Analytics Engineers, and Architects to align AI solutions with business needs, governed data access, platform realities, and technical constraints. • Contribute to hiring, onboarding, capability development, and team maturity within the AI engineering practice. • Follow established governance, privacy, safety, and responsible AI-use standards across the work of the team.

🎯 Requirements

• Advanced English level • Expected to demonstrate AI-native engineering habits appropriate to an AI Engineer role, including active use of approved AI-enabled tools and workflows for AI application development, orchestration design, prompt and retrieval integration, tool-calling workflows, API integration, testing, documentation, and reusable implementation patterns. Uses AI-assisted workflows to accelerate development, improve implementation quality, draft test cases, document workflow behavior, troubleshoot integration issues, and refine reusable components while maintaining human accountability for correctness, safety, maintainability, governed data access, and production usefulness. • Strong experience in AI application development using Python, SQL, PowerShell, and REST APIs, including workflow design and structured data (JSON) processing. • Hands-on experience with Microsoft Azure, including Azure AI Services, Azure OpenAI-compatible services, Azure API Management (APIM), Cosmos DB, and Microsoft Fabric for enterprise AI and data solutions. • Experience designing and implementing LLM-enabled and agentic applications, including RAG, prompt orchestration, tool calling, embeddings, context management, and workflow evaluation. • Strong knowledge of AI solution integration, cloud-native architectures, and scalable AI application development within Microsoft ecosystems. • Experience working with Databricks, Apache Spark, and PySpark to support AI, analytics, and data engineering workflows. • Proficient with Git, GitHub, and Azure DevOps for version control, collaboration, and CI/CD practices.

🏖️ Benefits

• Flexibility, with remote and hybrid work options (country-dependent) • Career advancement, with international mobility and professional development programs • Learning and development, with access to cutting-edge tools, training and industry experts • Medical, dental, and vision insurance for you and your family, plus employer contributions to Health Savings Accounts