Staff Engineer, Agentic Developer Platform

Jobtailor; Deutschland; Vor Ort; EUR 120.000 - 180.000; Vollzeit

Zusammenfassung

Jobtailor is seeking a senior engineer to design and own the core AI infrastructure, including shared systems, integration patterns, and runtime environments. You will define model selection, orchestration, data access layers, and deployment standards.

You will build an extensible platform enabling teams to expand capabilities with minimal involvement, while ensuring robust logging, evals, cost tracking, and monitoring. Strong leadership across functions is essential.

Qualifikationen

• 8+ years of professional software engineering experience in platform, infrastructure or tooling.
• Experience building shared systems that scale for other engineers.
• Hands-on with production AI systems (LLM integrations, agents, retrieval pipelines).
• Strong API and abstraction design with the right surface area vs complexity.
• Experience with MCP or similar integration patterns.
• Track record delivering greenfield technical work and early architectural decisions.
• Collaborative, transparent, and able to align cross-functionally without formal authority.
• Proven ability to bridge demos and production deployments of AI systems.
• Eager to work with product teams and across orgs to push AI platforms forward.

Aufgaben

• Design and own the company's core AI infrastructure and runtime environments.
• Make foundational decisions on models, orchestration, and data access layers.
• Engineer a platform that teams can extend independently for new use cases.
• Build observability, cost tracking, latency monitoring, and feedback loops.
• Develop the agent framework and skill library used across workflows.
• Define interfaces and composition patterns for scalable AI capabilities.
• Support multi‑agent workflows spanning systems and teams.
• Provide scaffolding and guidance to move ideas to working implementations.
• Develop internal tooling, documentation, and onboarding paths for accessibility.
• Create abstractions that lower AI development barriers without restricting advanced cases.
• Partner with teams and leadership to align AI infrastructure with strategy.
• Evolve standards for safety, reliability, and quality across the org.
• Contribute to org-wide technical discussions with a platform/infra lens.

Kenntnisse

AI infra design

Platform development

Infrastructure engineering

Developer tooling

API and abstraction design

Cross-functional leadership

Greenfield technical work

Logging and monitoring

Multi-agent orchestration

Technical program leadership

Tools

MCP Tool-Use Patterns

Jobbeschreibung

Responsibilities

• Design and own the company's core AI infrastructure: the shared systems, integration patterns, and runtime environments that all AI-powered work is built on top of.
• Make the foundational decisions that others will depend on, including model selection and abstraction, orchestration patterns, data access layers, and deployment standards.
• Design the platform so teams can extend it on their own, without needing your involvement for every new use case.
• Build the operational layer teams need to trust what they've deployed: logging, evals, cost tracking, latency monitoring, and feedback loops.
• Design and build the company's agent framework and skill library, the reusable building blocks that teams reach for when automating workflows, connecting systems, or extending AI capabilities into new areas.
• Define the interfaces, contracts, and composition patterns that let squads build new agents and skills confidently without reinventing core infrastructure.
• Ensure the framework supports a range of complexities, from simple single-step automations to multi-agent workflows spanning systems and teams.
• Help internal teams go from "we have an idea" to "we have a working implementation" by providing the technical scaffolding, guidance, and support.
• Build the internal tooling, documentation, and onboarding paths that make the platform genuinely accessible to team members across the company.
• Create abstractions that lower the floor for AI development without boxing in the complex cases.
• Act as a technical partner to teams adopting the platform, helping them get unblocked, apply patterns correctly, and avoid pitfalls early.
• Partner with Product to surface where AI capabilities can remove friction, accelerate workflows, or unlock things internal teams don't yet know are possible.
• Maintain a feedback loop with internal customers so the platform evolves around how people actually work, not how the roadmap assumed they would.
• Define how the company evaluates, adopts, and evolves AI capabilities responsibly, establishing standards for safety, reliability, and quality that hold across teams.
• Partner with engineering leadership to align AI infrastructure with broader architectural direction and long‑term system health.
• Contribute to org‑wide technical discussions, bringing a platform and infrastructure lens to decisions that affect how AI work gets done across the company.

Requirements

• 8+ years of professional software engineering experience, with meaningful depth in platform, infrastructure, or developer tooling.
• Experience building shared systems that other engineers build on, and an intuition for what makes internal platforms succeed or stall.
• Hands‑on experience with production AI systems (LLM integrations, tool‑using agents, retrieval pipelines, or comparable work), and a track record of enabling other builders to work with those systems confidently.
• Strong instincts for API and abstraction design, knowing how to expose the right surface area and hide the right complexity.
• Familiarity with MCP or similar tool‑use and integration patterns.
• A track record of scoping and delivering greenfield technical work, including making early architectural decisions that hold up over time.
• Collaborative and transparent by default, with the ability to lead cross‑functional alignment without formal authority.
• Clear‑eyed about the gap between AI that works in demos and AI that works in production, and experienced in closing it.
• Actively seeks out product and cross‑functional context, energized by the opportunity to push the work forward across teams, not just within engineering.
• Nice to Have: Experience with multi‑agent orchestration frameworks.
• Background in internal developer platforms, enablement engineering, or technical program leadership.
• Experience in defining and rolling out engineering standards across a multi‑team organization.

Demonstrates expertise in designing and building AI infrastructure, including shared systems and operational layers, while ensuring accessibility and extensibility for internal teams. Proven ability to lead cross‑functional collaboration and establish engineering standards that enhance AI capabilities across the organization.

Highest‑signal resume keywords

• AI Infrastructure Design
• Production AI Systems Experience
• API and Abstraction Design
• Cross‑Functional Collaboration
• Greenfield Technical Work

Hard Skills

• Software Engineering
• Platform Development
• Infrastructure Engineering
• Developer Tooling
• AI Systems Integration
• MCP Tool‑Use Patterns
• Multi‑Agent Orchestration
• Architectural Decision Making
• Logging and Monitoring
• Feedback Loop Implementation

Soft Skills

• Collaborative Leadership
• Transparent Communication
• Problem‑Solving
• Technical Guidance
• Cross‑Functional Alignment

Industry Keywords

• Internal Developer Platforms
• Enablement Engineering
• Technical Program Leadership
• Engineering Standards
• AI Capabilities Evaluation