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IFS

Cloud-based ERP, EAM, FSM, ESM solutions

Senior AI/Machine Learning Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timePalo Alto, CA, USAHybrid

About the Job

Requirements

  • At least 5 years of software engineering experience, including at least 2 years building AI/ML-powered applications in production environments.
  • Strong proficiency in Python and experience designing backend systems and APIs.
  • Experience with large language models, agent frameworks, retrieval-augmented generation architectures, vector databases, embeddings, and AI orchestration platforms.
  • Hands-on experience with technologies such as OpenAI, Azure AI, Anthropic, Hugging Face, LangChain, LangGraph, Semantic Kernel, Pinecone, Weaviate, or equivalent platforms.
  • Solid understanding of software architecture, cloud-native development, microservices, and scalable system design.
  • Experience building and operating production applications in cloud environments.
  • Strong problem-solving, debugging, and performance optimization skills.
  • Effective communication and collaboration skills.

Responsibilities

  • Design and implement scalable AI services and platform capabilities that support intelligent agents and enterprise workflows.
  • Build reusable software development kits, application programming interfaces, orchestration layers, and shared services that accelerate AI application development.
  • Contribute to architectural discussions and technical design reviews.
  • Develop solutions that meet reliability, observability, security, and scalability requirements.
  • Design and implement production-grade solutions using large language models, embeddings, retrieval-augmented generation architectures, vector databases, memory systems, and agent orchestration frameworks.
  • Evaluate and integrate emerging AI technologies, foundation models, and agent frameworks where appropriate.
  • Develop prompt engineering approaches, evaluation strategies, and guardrails to improve quality, safety, and reliability.
  • Implement evaluation frameworks and AI quality metrics to measure system performance and business outcomes.
  • Optimize latency, accuracy, cost, and scalability of deployed AI systems.
  • Deliver complex AI initiatives from design through production deployment.
  • Apply best practices for testing, continuous integration and continuous delivery, infrastructure automation, monitoring, and operational readiness.
  • Troubleshoot performance issues and conduct root-cause analysis across distributed AI services and integrations.
  • Ensure solutions align with enterprise requirements for governance, compliance, and security.
  • Collaborate with engineers, product managers, architects, and domain experts to translate business requirements into scalable technical solutions.
  • Provide technical guidance and share knowledge with team members.
  • Contribute to technical documentation, design reviews, and engineering best practices.
  • Support continuous improvement of development processes, tooling, and platform capabilities.

Desired Qualifications

  • Experience building agentic AI systems, copilots, multi-agent workflows, or autonomous enterprise applications.
  • Experience with AI evaluation frameworks, large language model observability, AI governance, and responsible AI practices.
  • Experience with Azure, Amazon Web Services, or Google Cloud Platform AI ecosystems.
  • Experience integrating enterprise platforms such as enterprise resource planning, customer relationship management, IT service management, human resources, finance, or developer ecosystems.
  • Experience mentoring junior engineers or supporting technical onboarding.

About the Company

IFS

Cloud-based ERP, EAM, FSM, ESM solutions

IFS provides cloud-based enterprise software for large organizations, covering ERP, EAM, FSM, and ESM. Customers license subscriptions to access modules that handle operations, asset management, field service, and internal service workflows, with implementation and ongoing support. It stands out by offering a broad, integrated suite tailored to multiple industries and backed by a global services network. The goal is to help enterprises optimize operations, improve productivity, and advance sustainability with a scalable cloud platform.

Company size
5,001-10,000
Company stage
Growth Equity (Non-Venture Capital)
Total funding
$3.3B
Headquarters
Linköpings kommun, Sweden
Founded
1983

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