Summary: Dynatrace is seeking a Lead Data Scientist specializing in Large Language Models to design, build, and scale generative AI capabilities for enterprise-grade use cases, owning the end-to-end LLM stack. Highlights: 1. Lead the design, build, and scaling of generative AI capabilities 2. Own the end-to-end LLM stack from data ingestion to optimization 3. Provide deep technical mentorship on prompting, retrieval design, and evals **Your role at Dynatrace** -------------------------- Dynatrace makes it easy and simple to monitor and run the most complex, hyper\-scale multicloud systems. Dynatrace is a full stack and completely automated monitoring solution that can trackevery user, every transaction, across every application. Our team is looking for a Lead Data Scientist specialized in Large Language Models (LLMs) to design, build, and scale generative AI capabilities for real\-world, enterprise\-grade use cases. In this hands\-on technical leadership role, you’ll own the end\-to\-end LLM stack, from data/knowledge, Ingestion and retrieval to prompt and tool\-use architecture, evaluation frameworks,safety/guardrails, and cost/latency optimization. **Your Tasks** * Own the LLM system architecture: Retrieval pipelines, prompt/tool design, routing/fallbacks, safety layers, and telemetry, optimized for quality, latency, and cost. * Establish technical standards for RAG: content ingestion, chunking/windowing, hybrid retrieval, reranking, query understanding, and structured output contracts. * Define evaluation strategy: Create a rigorous eval suite covering answer correctness, attribution/grounding, toxicity/safety, privacy leakage, determinism, latency, and cost. * Formalize LLMOps: Versioning for prompts/datasets/models, experiment governance, prompt and dataset registries, and promotion criteria from dev \- staging \- prod. * Drive tool/agent design: API schema design for function calling, error handling, recovery strategies, self\-correction, and guardrail integration. * Make build\-vs\-buy calls: Weigh managed providers vs. open\-source/self\-hosted, considering performance, cost, IP, privacy, and compliance. * Mentoring: Provide deep technical mentorship on prompting, retrieval design, evals, and safe deployment; lead reviews of prompts, pipelines, and evaluation reports. **Hands\-on Data Science** * Implement end\-to\-end RAG systems: ingestion \- chunking \- embeddings \- hybrid search \- rerank \- prompt assembly \- tool calls \- post\-processing. * Engineer robust prompts/tools: reusable templates, multi\-turn strategies, structured outputs via JSON Schema/Pydantic. * Select/tune models: foundation models, embeddings, rerankers; apply LoRA/PEFT or distillation when justified. * Build eval corpora: golden sets, KPIs for accuracy, groundedness, deflection, tool success. * Implement guardrails: PII/PHI detection, policy prompts, jailbreak resistance, filters, safety scorecards. * Productionize: ship resilient services with analytics, alerts (drift, quality, cost), SLOs, etc. * Optimize for scale: token, latency, cost; caching, context packing, batching, speculative decoding, routing by intent **What will help you succeed** ------------------------------ **Minimum requirements:** * Advanced CS/AI/ML degree or equivalent, strong ML background. * 7\+ years DS/ML, 3\+ years NLP /LLMs, shipped production systems. * Python and core ML stack: 5\+ years of professional Python. * Data engineering for unstructured data (3\+ years): text processing, parsing, embedding\- friendly preprocessing. * Proven RAG expertise (1\+ years): embeddings, retrieval, reranking, chunking. * Evaluation depth (1\+ years): offline/online evals for accuracy, grounding, safety. * Safety/privacy (1\+ years): moderation, PII/PHI redaction, policy enforcement. * LLMOps (1\+ years): prompt/version management, experiment tracking, monitoring. * Excellent communication: explain trade\-offs, drive data decisions. **Desirable experiance:** * Serving/scaling: vLLM/TGI, Ray Serve, Triton; GPU/CPU trade\-offs. * Tuning/distillation: LoRA/PEFT, safety alignment, synthetic data. * Domain: observability, support systems, multilingual, regulated environments. * Cloud/security: Snowflake/AWS, managed vs self\-hosted. * Experience with graph\-based knowledge bases (e.g., GraphDB, Neo4j) and knowledge graphs to complement RAG systems with entity modeling and relationship\-aware retrieval. **Why you will love being a Dynatracer** ---------------------------------------- * Working models that offer you the flexibility you need, ranging from full remote options to hybrid ones combining home and in\-office work * A team that thinks outside the box, welcomes unconventional ideas, and pushes boundaries * An environment that fosters innovation enables creative collaboration and allows you to grow * A globally unique and tailor\-made career development program recognizing your potential, promoting your strengths, and supporting you in achieving your career goals * A truly international mindset with Dynatracers from different countries and cultures all over the world, and English as the corporate language that connects us all * A culture that is being shaped by our global team’s diverse personalities, expertise, and backgrounds * A relocation team that is eager to help you start your journey to a new country, always there to support and by your side. If you need to relocate for a position you’re applying for, we offer you a relocation allowance and support with your visa, work permit,accommodation . **Note to Recruiters and Agencies** : Thank you for your interest in Dynatrace. Please note that **we do not accept unsolicited agency resumes** —do not forward them via our website or directly to Dynatrace employees. Dynatrace will not pay fees for unsolicited resumes, and any resumes received this way will be considered the property of Dynatrace. **Benefits and work\-life perks** --------------------------------- We offer best\-in\-class core rewards, including paid time off, financial security benefits, retirement savings plans, and health insurance. Beyond that, you’ll get other benefits and work\-life perks designed to make your ride with us even more rewarding. #### **Mental health support** Our Employee Assistance Program, powered by Telus Health, offers support for you and your family members. #### **Wellness Days** Four company\-designated extra paid days off for you to recharge batteries. #### **Flexibility** Our hybrid working model and flexible working hours offer you the flexibility you need. #### **Employee Stock Purchase Plan** Purchase company stock ( NYSE:DT ) at a discounted price and become a shareholder. #### **Learn \& develop** Company\-wide learning perks, designated team's learning days, and more. #### **Volunteering day** A day of paid volunteer time to support a community or cause you care about. #### **Regular team events** We host Global Culture Parties, Family \& Friends at Work Day, Global Breakfasts, Green Weeks, Pride Month, and beyond! #### **International vibe** Most of our offices and teams are proudly multicultural. English is our shared language, but we embrace and learn from each other's cultures. Rewards vary depending on your employment type. Some benefits and perks also differ by location — explore your city to see what’s available there. **About Dynatrace** ------------------- Dynatrace (NYSE: DT) is the leading AI\-powered observability and security platform. We're advancing observability for today's digital businesses, helping transform modern digital ecosystems' complexity into powerful business assets. Our AI\-driven insights cut through the noise, allowing customers to focus on what truly matters by automating manual tasks and resolving issues with pinpoint accuracy. Dynatrace offers simplicity, clarity, and reliability at scale to ensure teams can make informed decisions, minimize downtime, and drive their business forward with confidence.