3 days ago
Remote, Poland +2 moreStaff+
Responsibilities
- Design and architect AI-powered systems using LLMs, retrieval-augmented generation, agentic workflows, orchestration patterns, and enterprise data.
- Build scalable, secure, maintainable software platforms and cloud-native services that integrate models, tools, retrieval systems, workflows, and business processes.
- Prototype and validate new AI technologies through rapid proofs of concept, experimentation, measurement, and iteration.
- Bring AI solutions into production across scoping, design, development, testing, deployment, monitoring, governance, and continuous improvement.
- Establish evaluation, benchmarking, testing, observability, and quality practices for AI systems.
- Lead technical design discussions and architecture reviews while driving engineering best practices across teams.
- Develop reusable AI capabilities and frameworks and mentor engineers.
- Collaborate with product teams, architects, customers, partners, and domain experts to identify opportunities and deliver measurable business impact.
- Influence IFS’s AI strategy and long-term technology direction through hands-on delivery, customer engagement, industry events, and partner collaboration.
Requirements
- Bachelor’s degree in computer science, software engineering, AI, data science, or a related field; a master’s degree is advantageous.
- At least 8 years of professional experience in AI, machine learning, and/or software engineering, with a proven record of successfully delivered projects.
- Demonstrable hands-on experience designing, building, and shipping production AI applications and bringing incubated AI solutions into production.
- Strong programming skills 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, infrastructure as code, deployment pipelines, model operations, and observability.
- Experience designing AI-driven architectures using LLMs, RAG, agentic workflows, orchestration patterns, and enterprise data sources.
- Experience leading technical discussions, influencing architecture and technology strategy, mentoring engineers, and aligning cross-functional teams.
- Ability to explain complex technical concepts to technical and non-technical audiences and translate business problems into technical strategies and measurable outcomes.
- Experience with at least two desirable technology areas, including LLM serving, AI platforms, foundation models, agentic AI frameworks, AI evaluation and observability, cloud infrastructure, model development, or GPU infrastructure.
- Experience with enterprise AI platforms, developer tooling, enterprise software domains, customer-facing demonstrations, open-source AI communities, or Microsoft Azure, AWS, or Google Cloud AI services is desirable.
Benefits
- Flexible hybrid work opportunities that support varied work arrangements while encouraging in-person collaboration and community.
- Opportunity to build production AI systems and shape next-generation AI-native enterprise software at a global company.
- Opportunity to collaborate with customers, partners, industry communities, and colleagues across a diverse international organization.
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.