Lead Data Scientist

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

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.

• 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 .