3 days ago
Remote, Spain or Madrid, SpainStaff+
Responsibilities
- Design and architect enterprise AI systems using LLMs, retrieval-augmented generation, agentic workflows, and orchestration patterns.
- Build production-ready software platforms and cloud-native services that integrate models, tools, retrieval systems, enterprise workflows, and data.
- Prototype and validate AI technologies through proofs of concept, experimentation, measurement, and iteration.
- Establish evaluation, testing, benchmarking, monitoring, observability, quality, and continuous-improvement practices.
- Lead technical design discussions and architecture reviews, drive engineering best practices, and influence long-term AI strategy.
- Mentor engineers and develop reusable AI capabilities and frameworks.
- Collaborate with product teams, customers, partners, architects, and domain experts to deliver measurable business impact.
- Engage in customer-facing innovation, industry events, partner collaboration, and technical direction-setting.
Requirements
- Bachelor’s degree in computer science, software engineering, AI, data science, or a related field; a master’s degree is advantageous.
- 8+ years of professional experience in AI, machine learning, and/or software engineering.
- Demonstrated experience bringing incubated AI solutions through scoping, design, development, testing, deployment, and monitoring into production.
- Strong programming ability in one or more of Python, Golang, C#, or TypeScript.
- Experience with context engineering, retrieval architecture, embeddings, vector databases, search technologies, and retrieval optimization.
- Strong backend engineering fundamentals including APIs, distributed services, cloud-native architectures, integration, automation, and security.
- Background in DevOps and MLOps/LLMOps, including infrastructure-as-code and package management tools such as Terraform and Helm Charts.
- Experience designing AI-driven architectures with LLMs, RAG, agentic workflows, orchestration patterns, and enterprise data sources.
- Understanding of AI system lifecycle activities including evaluation, deployment, monitoring, governance, and continuous improvement.
- Experience leading technical discussions, influencing architecture and technology strategy, mentoring engineers, and aligning teams.
- Ability to work with customers and stakeholders, prototype rapidly, explain complex technical concepts, and translate business problems into execution plans.
- Experience with two or more desirable technologies or areas including LLM serving, AI platforms, foundation models, agentic AI frameworks, evaluation and observability tools, cloud infrastructure, model development, AI accelerators, enterprise AI platforms, or cloud AI services.
- Experience with technologies such as vLLM, LiteLLM, KServe, Cohere, OpenAI, Anthropic, Llama, Mistral, DeepSeek, LangGraph, PydanticAI, Semantic Kernel, CrewAI, AutoGen, MCP, MLflow, DeepEval, Ragas, Promptfoo, Langfuse, Kubernetes, Docker, Helm, Terraform, Hugging Face Transformers, PEFT, or LoRA is highly desirable.
- Experience with Microsoft Azure, AWS, or Google Cloud AI services and enterprise software domains is advantageous.
- Hands-on production AI application experience is required; experience limited to using AI assistants for software development does not meet the requirements.
Benefits
- Flexible and hybrid work opportunities.
- Inclusive workplace experiences and a global, diverse environment.
- Opportunity to work on AI-native enterprise software with worldwide customer impact.
- Opportunities for customer engagement, industry events, partner collaboration, open-source contributions, technical communities, conferences, and publications.
Tech Stack
Categories
About IFS
IFS builds IFS Cloud, an enterprise suite covering ERP, EAM, FSM, SCM, and project/service management for manufacturers and asset‑intensive organizations. Its business model centers on software subscriptions and services for cloud and hybrid deployments, plus industry-specific modules and consulting. Founded in 1983 and headquartered in Linköping, Sweden, the company is privately held under EQT ownership and operates globally across industrial and service-focused markets.