Senior AI Engineer

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🕒 Junho 24

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NetCraftsmen, now BlueAlly

SiteLinkedInTodas as Vagas

51 - 200 funcionários

💼 Consultoria

📦 Logística

📣 Marketing

Consulting • Logistics • Marketing

A NetCraftsmen foi adquirida pela BlueAlly em março de 2022. Na BlueAlly, nossa missão é tornar a tecnologia mais acessível, mais certa e mais impactante para todas as organizações. Em uma era digital onde a tecnologia avançada muitas vezes traz complexidade adicional, adotar TI de última geração pode ser uma tarefa de nível superior. A BlueAlly oferece um conjunto completo de serviços gerenciados e de consultoria/profissionais de TI que permitem que as organizações prosperem com os benefícios da tecnologia avançada.

Descrição

• Design, build, and operate enterprise AI systems across our client portfolio. • Work end-to-end across the AI stack — from inference engines and platform infrastructure up through application-level engineering. • Lead workstreams independently and mentor more junior engineers. • Engage directly with client architects, data scientists, application teams, and executives.

🎯 Requisitos

• 7+ years of software, data, or infrastructure engineering, with 3+ years specifically working with modern AI / LLM systems. • Production-quality Python at engineering level — testing, code review, version control fluency, and shipping code that other engineers depend on. • Deep production Linux experience, including system internals, performance tuning, and troubleshooting. • Deep proficiency with Docker — image build, registry management, runtime tuning, and container security. • Strong server-platform skills including CPU/GPU topologies, PCIe, BMC management, BIOS/firmware lifecycle, and physical-to-logical troubleshooting. • Hands-on experience deploying and operating one or more of HPE PCAI, Dell AI Factory, or Nutanix Enterprise AI. • Production experience deploying, tuning, and operating vLLM. • Working knowledge of multiple inference and model-serving frameworks beyond vLLM, with the ability to choose and tune the right tool for each workload. • Hands-on experience with high-throughput, low-latency storage and network fabrics for AI workloads — including RDMA-class interconnects, parallel/object storage tiers, KV cache management, and Dynamo-style disaggregated serving. • Practical experience operating MLOps tooling and patterns — model registries, deployment pipelines, GitOps, lineage, and rollback. • Hands-on experience deploying, tuning, and integrating vector databases and RAG pipelines, including the application-level engineering that sits on top of them. • Production experience designing system prompts, structured output, function calling, and tool-using LLM patterns. • Demonstrated experience designing LLM evaluation harnesses — golden sets, regression suites, and quality/cost metrics. • Demonstrated ability to engage directly with client stakeholders — running working sessions, presenting recommendations, and translating technical detail for non-technical audiences. • Strong written and verbal communication — clear reference architectures, runbooks, and incident reports. • Track record of mentoring more junior engineers and raising team technical quality through code review and pairing. • Networking fundamentals: TCP/IP, DNS, load balancing, VLANs, and firewall administration. • Comfort working across multiple concurrent client environments and managing competing priorities under SLA.