Job TitleOwn the end-to-end technical design for large-language-model (LLM) and generative-AI solutions across NVIDIA, AWS, Azure and GCP stacks.Job DescriptionKX software powers the time-aware data-driven decisions that enable fast-moving companies to outpace competitors, realizing the full potential of their AI investments. The KX platform delivers transformational value by addressing data challenges related to completeness, timeliness and efficiency, ensuring companies understand change over time and can achieve faster, more accurate insights at any scale, cost-effectively.KX is essential to the operations of the world's top investment banks, aerospace and defence, high-tech manufacturing, healthcare and life sciences, automotive and fleet telematics organizations. The company has established offices and a robust customer base across North America, Europe, and Asia Pacific.Overview Of The RoleOwn the end-to-end technical design for large-language-model (LLM) and generative-AI solutions across NVIDIA, AWS, Azure and GCP stacks.
You will translate business use-cases into secure, scalable architectures, lead reference implementations, and mentor delivery teams for enterprise deployments—especially in financial-services environments.Key ResponsibilitiesShape multi-cloud architectures for training, fine-tuning and serving LLMs (e.g., NeMo, Bedrock, Azure OpenAI, Vertex AI).Define MLOps/GitOps patterns for model lifecycle, vector–DB indexing, retrieval-augmented generation (RAG) and guard-railing. Benchmark and cost-optimize GPU, Grace Hopper and CPU clusters (TCO & carbon impact).Build production pipelines in Python (FastAPI, LangChain, Ray, Triton, Airflow).Establish security and compliance controls (encryption, IAM, SOC 2, FINRA,GDPR).Support pre-sales and proofs-of-concept with capital-markets clients.SkillsProgrammingPython (must-have)JavaScript / TypeScript (for web + full-stack AI apps)Writing clean, testable codeMath & ML BasicsLinear algebra (vectors, matrices, embeddings)Probability & statisticsML concepts: overfitting, loss functions, training vs inferenceData SkillsData cleaning & preprocessingPandas, NumPySQL basicsEssential Experience10-15 yrs building cloud-native data or ML platforms on AWS, Azure and/or GCP. Deep expertise in Python plus one of Go, Java or C++.Hands-on with embedding models, tokenizer optimisation, prompt orchestration and OpenAI/Anthropic APIs.
Prior delivery of enterprise Gen-AI systems (risk analytics, chatbots, document generation etc.).Solid grounding in distributed systems (K8s, service mesh, Kafka, Redis, GPU scheduling).Preferred QualificationsExperience with kdb+/q, ClickHouse or similar time-series stores. Contributions to open-source AI frameworks or NVIDIA NGC containers. Working knowledge of SRE/FinOps best practice.Location & Workplace TypeThis position takes on a Hybrid working model based in Ontario, Canada.Why Choose KXData Driven: We lead with instinct and follow fact.Naturally Curious: We lean in, listen and learn fast.All In: We take ownership, take on challenges and give it our all.BenefitsCompetitive SalaryIndividually tailored training and skills developmentPrivate healthcare package and Employee Assistance ProgrammeEnhanced maternity and paternity packageWellness Days and Volunteer DaysJob InfoJob Identification 11353Job Category KXLocations 31 Lakeshore Road East, Mississauga, Ontario, L5G 4V5, CA