• Design and deliver production-grade agentic systems, from multi-agent orchestration to the AI services and models that power them • Assess fit of agentic solutions per use case, being intentional in system design • Design the most suitable orchestration pattern per use case • Evaluate and recommend the best suited agent development framework • Engineer multi-step agent workflows that are reliable, auditable and modular, supporting both linear and non-linear control flows • Implement agent memory and state management systems • Optimise context assembly for each agent interaction • Evaluate and select the most appropriate foundation models, embeddings and context-specific model variants; apply fine-tuning or adaptation where needed • Implement guardrails to ensure operation within ethical, legal, brand boundaries • Build services for agent use, including ML models, GenAI and task-specific APIs • Process multi-modal data using appropriate embeddings and vector retrieval • Build, evaluate and maintain robust RAG and / or GraphRAG pipelines • Implement fallback strategies (e.g., retries, backup tools, escalation, safe exits) • Build and integrate MCP servers to expose and consume data and AI services • Use Google's A2A protocol to support independent agent communication, designing composable service boundaries and appropriate integration patterns • Containerise applications (Docker) – our platform team manages K8s • Apply AgenticOps practices, including evaluation, observability, guardrails, security, performance optimisation, CI/CD, versioning, rollback, drift detection • Design and implement testing strategies for non-deterministic behaviour • Stay abreast of the latest AI research trends and integrate them into our products • Maintain documentation for architectures, APIs and operational procedures • Communicate progress, blockers, technical approaches, challenges and potential solutions to technical colleagues and non-technical stakeholders.

• Developing machine learning models using natural language process that will be integrated into automated processes. • Building and training models, deploying model pipelines, and implementing algorithms to extract insights from unstructured data. • Troubleshooting and providing technical solutions to resolve issues. • Utilizing Python, SQL, and NLP/machine learning technologies to perform conversational analytics. • Analyzing structured and unstructured data and building predictive models using various approaches. • Searching through large data sets and transforming data for analysis. • Creating reports and presentations to translate complex analytical results into business impacts for executive leaders. • Documenting and maintaining codebase standards, contributing to ongoing quality and reliability improvements.

Role Description Brainspring Learning Centers (Brainspring.com), the leaders in Structured Literacy, is seeking motivated, dedicated, enthusiastic people who are passionate about making a difference. We are expanding our community of expert reading tutors with the goal of delivering high quality virtual instruction to students and families nationwide. Why Join the Brainspring Team? - Free Professional Development - Competitive Pay - Flexible Scheduling - Bonus Incentives for Recruiting Students - Opportunities for Advancement Brainspring Tutors can complete the Orton-Gillingham Dyslexia Specialist Certification practicum free of charge ($4,000 approx. value) while tutoring. Our Phonics First® programs are accredited through both the IDA (International Dyslexia Association) under their Knowledge and Practice Standards for Teachers of Reading and through IMSLEC (International Multisensory Structured Language Education Council) at their Teaching Level and Instructor of Teaching Level. Up to 4 grad credits are available for purchase upon the successful completion of the certification practicum. Qualifications - Bachelor's degree (Education related preferred) - Weekday tutoring availability, particularly during after-school hours - Completion of Brainspring's Phonics First® or Structures® course within the last year or a certified Orton-Gillingham Dyslexia Specialist Requirements - All candidates are subject to a background check. Compensation - $30+/hr based on education, experience and availability Full-Time/Part-Time - Independent Contractor

Your role at DynatraceDynatrace 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 succeedMinimum 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 .