Forward Deployed Engineer

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

📋 Description

• Collaborate closely with product teams to comprehend business workflows and pinpoint areas where AI can provide assistance.

• Guide technical exploration and differentiate between business-process obstacles and their symptoms.

• Discover opportunities to implement or enhance current AI services.

• Assist product teams in the design and development of AI-centric applications.

• Collect and document requirements for new AI services.

• Work alongside engineering teams to outline, design, and create new AI services.

• Engage directly with data pipelines, model training, serving, MLOps tools, and product integrations.

• Release initial versions swiftly and refine them through monitoring, feedback loops, and ensuring production-grade reliability.

• Convert product challenges and business needs into actionable items for the AI services roadmap.

• Partner with product owners, business stakeholders, and engineering leaders.

• Clearly articulate technical trade-offs to non-technical audiences.

• Link IFS R&D's AI capabilities with product teams and offer field insights for forthcoming developments.

⛳️ Requirements

• Over 5 years of experience in software engineering.

• Strong practical skills in building and deploying production systems.

• Proficient in Python and open to working with other languages and existing customer codebases.

• Experience in constructing and managing cloud-native services.

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

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

• Proficient in creating agentic applications using tools, APIs, and orchestration frameworks.

• Hands-on experience with MCP is highly preferred.

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

• Strong background with REST APIs, authentication/authorization, external systems, data contracts, and complex integrations.

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

• Comfortable working with relational, document, vector, and object storage systems.

• Understanding of event-driven and distributed systems architecture.

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

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

• Ability to transform unclear business challenges into defined, delivered systems.

• Capability to convey technical concepts and trade-offs effectively to non-technical stakeholders.

• Experience collaborating with or as part of platform or infrastructure teams.

• Ability to engage directly with customers and stakeholders, rapidly prototype, and implement solutions.

• Proven hands-on experience in designing, constructing, and deploying production AI applications.

🏝️ Benefits

• Flexible and hybrid work options.

• Inclusive workplace experiences.

• Environment focused on sustainability.

• A global and diverse work environment.

• Opportunity to engage with AI-driven enterprise software and make a significant global impact.