Forward Deployed Engineer

This is a fully remote position, open to applicants in Spain.

📋 Description

• Integrate seamlessly with product teams to comprehend business workflows and identify areas where AI can provide assistance.

• Lead technical investigations to differentiate genuine business-process obstacles from mere symptoms.

• Align existing AI services with product challenges and assist in the design and development of AI-centric applications.

• Collect and document requirements when there is no suitable existing AI service.

• Collaborate with engineering teams focused on AI services to define, design, and create new services.

• Engage directly with data pipelines, model training and deployment, MLOps tools, and product-workflow integrations.

• Rapidly deliver initial versions and reinforce them with monitoring, feedback loops, and production-grade reliability.

• Convert product team pain points and business needs into actionable input for the AI services roadmap.

• Coordinate with product owners, business stakeholders, and engineering leads while discussing technical trade-offs.

• Connect IFS R&D’s AI capabilities with product teams and leverage field insights to guide future development.

⛳️ Requirements

• Over 5 years of experience in software engineering.

• Strong practical skills in building and deploying production systems.

• Proficient in Python and eager to work with other languages and existing customer codebases.

• Experience in developing and managing cloud-native services.

• Familiarity with Azure, especially AKS, Blob Storage, Key Vault, and Azure-hosted AI/model services.

• Background in integrating LLMs and AI services into production applications, covering model APIs, authentication, gateways, reliability, latency, cost, and observability.

• Experience in building agentic applications using tools, APIs, and orchestration frameworks.

• Prior hands-on MCP experience is highly preferred.

• Practical experience in designing production RAG and retrieval systems, including embeddings, vector databases, indexing, retrieval quality, and evaluation.

• Solid experience with REST APIs, authentication/authorization, external systems, data contracts, and troubleshooting complex integrations.

• Proficient in Docker, Kubernetes, Helm, GitOps/ArgoCD, and Terraform or similar infrastructure-as-code tools.

• Comfortable working with relational, document, vector, and object stores.

• Understanding of event-driven and distributed systems architecture.

• Knowledge of AI evaluation, observability, monitoring, failure modes, and quality/latency/reliability/cost trade-offs.

• Experience in building and maintaining production ML/data systems, beyond just notebooks or prototypes.

• Familiarity with working in or alongside platform or infrastructure teams.

• Ability to engage directly with customers and stakeholders, transform ambiguous business challenges into technical solutions, rapidly prototype, and productionize solutions.

• Strong communication skills with non-technical stakeholders.

• Proven hands-on experience in designing, building, and delivering production AI applications.

🏝️ Benefits

• Flexible and hybrid work options.

• Inclusive workplace culture.

• Opportunities to work in a global, diverse setting.

• Commitment to sustainability efforts.

• Chance to engage with AI-driven solutions that have a global impact.