• Manages AI platforms and environments, including access provisioning, governance controls, and policy enforcement (e.g., DLP, security, and compliance) • Develops reusable components (e.g., prompts, connectors, APIs, templates) to accelerate AI solution delivery and promote standardization across use cases • Designs and maintains the foundational AI infrastructure, frameworks, and observability capabilities (telemetry, monitoring, metrics) required for scalable, reliable, and governed AI operations • Enforces security protocols, data handling rules, and role-based access controls in collaboration with InfoSec and Legal • Oversees workspace configuration, user provisioning, single sign-on (SSO), and licensing • Connects AI tools with core enterprise software (like HRIS, CRMs, and document repositories) • Creates internal training materials, troubleshooting guides, and tracks AI usage metrics to drive value realization • Tracks platform performance, API error rates, and token consumption to optimize operational costs

• Architect and implement production-ready AI solutions involving LLMs, transformer-based models, retrieval systems, agentic workflows, and AI agents for generative tasks and automation. • Design and iterate on prompts, workflows, and RAG pipelines to improve accuracy, cost-efficiency, latency, and safety. • Design and build multi-step agentic systems that break down complex tasks, invoke external tools or APIs, manage state, and handle reasoning chains robustly. • Deploy models and GenAI pipelines in production environments (API, batch, streaming), ensuring reliability and scalability. • Build and maintain evaluation frameworks to measure model grounding, factuality, latency, and cost. • Develop and integrate guardrails (e.g., prompt-injection protections, content moderation, output validation), and safeguards for agent loops (e.g., loop prevention, tool call limits, state validation). • Collaborate cross-functionally with Product, Engineering, and ML Ops to deliver high-quality AI features end-to-end.

• We are building the newsroom of the future in Germany’s largest financial portal. • AI handles routine tasks so our editorial team can focus on what truly matters: context, analysis, and point of view. • AI-driven workflows for market reports, earnings recaps, economic updates, and much more • Development of multiple n8n flows as a central editorial asset • Wide selection of tools, API integration, quality assurance – end-to-end content repurposing at scale: articles, newsletters, and social media.

Role Description Block is building toward one of the most ambitious technical visions in our history: an AGI-enabled entity that fundamentally transforms how we deliver economic empowerment. We're assembling a world-class team of AI experts to design and ship autonomous agents and agentic workflows that operate across Square, Cash App, and the broader Block ecosystem. This work is about creating solutions—you'll be building AI that acts, decides, and completes real tasks for real users from across all of Block's business functions. As a Principal Engineer, you'll join as a senior individual contributor with significant technical leadership responsibilities. - Ship, architect, build, and own end-to-end delivery of autonomous agents and agentic workflows that deliver real business value for Block, ensuring reliability, safety, and performance at scale. - Design agent orchestration systems including planning, tool use, memory, evaluation, and multi-agent coordination at production scale. - Integrate and optimize frontier LLMs into agent architectures, making decisions on model selection, fine-tuning, prompt engineering, and context retrieval strategies. - Drive deeper model optimization work (fine-tuning, distillation, RLHF) where it unlocks agent capability or efficiency. - Lead detailed technical planning by breaking down ambitious objectives into concrete, sequenced tasks with clear ownership and execution paths. - Provide technical mentorship and guidance to engineers across experience levels, elevating team capabilities through code review, pairing, and knowledge sharing. - Partner closely with technical and non-technical stakeholders to translate business objectives into agent-powered product experiences. - Keep Block at the frontier by continuously evaluating emerging AI capabilities and making pragmatic tradeoffs across model performance, latency, cost, and user experience. - Foster a culture of technical excellence, high-quality delivery, rapid experimentation, and learning within your team and beyond. Qualifications - 15+ years of experience in software engineering or machine learning, with recent professional experience building autonomous agents or agentic workflows in production. - Deep experience building autonomous agents or agentic workflows in production environments—not just prototypes or demos. - Fluency in the core primitives of agentic systems: context management, planning, tool use, memory, evaluation, and multi-step reasoning. - Experience bringing frontier LLM capabilities into production products, with hands-on experience in prompt engineering, retrieval-augmented generation, and model optimization. - A track record of taking AI-powered products from zero to scale in fast-paced, product-driven environments, with the judgment that comes from operating in production. - Strong software engineering fundamentals with the ability to write production-quality code and make sound architectural decisions. - Experience providing technical leadership within teams—you've shaped technical direction, driven execution, and elevated others. - Product-minded engineering approach—you think in terms of user outcomes, not just model metrics. - Excellent collaboration and communication skills, with ability to build alignment across engineering, product, and design. - Comfort navigating extreme ambiguity in a domain that's evolving weekly. - Alignment with Block's mission of economic empowerment and using technology to create access and opportunity. Bonus Points For - Experience at leading AI organizations with a track record of translating research into production agent systems. - Background building or scaling agentic products at startups (including early-stage or pivoting companies). - Experience with model fine-tuning, distillation, or RLHF to improve agent performance. - Familiarity with agent evaluation, safety, and alignment challenges in production contexts. Benefits - Remote work - Medical insurance - Flexible time off - Retirement savings plans - Modern family planning