AI Engineer

Job not on LinkedIn

🕒 3 days ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Insight Softmax Consulting

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2016

💼 Consulting

🤖 Artificial Intelligence

🤝 B2B

Consulting • Artificial Intelligence • B2B

Insight Softmax Consulting is a data-focused consulting firm that combines data science, software engineering, and high-performance computing to solve business and research problems end-to-end. They emphasize defining business problems first and then delivering solutions in data analytics, AI/ML (including generative AI and LLM training), and last-mile HPC infrastructure (cloud-native HPC, accelerated computing for CFD and advanced scientific workloads). The company also offers open-source expertise and services to make powerful compute and AI capabilities accessible to enterprises and research organizations. Offices are listed in San Francisco, USA and Zürich, Switzerland.

📋 Description

• Deploy and operate LLM inference services on Kubernetes and bare-metal GPU clusters • Implement model serving, autoscaling, GPU scheduling and performance tuning • Build and operate AI gateway and routing layers with tenant keys, model pools, quotas, rate limits, caching, failover and usage metrics • Implement RAG pipelines, agentic workflows, evaluation harnesses and customer-facing APIs • Write production-quality Python services and infrastructure automation • Instrument AI services for observability, including latency, throughput, token and cost accounting, and quality signals • Run benchmarks and load tests and convert results into tuning changes and capacity recommendations • Integrate AI services with customer identity, security and data systems • Document deployments and hand over runbooks to customer and internal operations teams • Support pre-sales, internal platform work and knowledge sharing • Work directly in customer environments and deliver deployable systems, documentation and automation

🎯 Requirements

• At least 4 years of software or platform engineering experience • At least 2 years building and running LLM or ML services in production • Hands-on experience with at least one inference server, such as vLLM, TensorRT-LLM, Triton or llm-d • Experience running GPU workloads on Kubernetes • Strong Python skills; ability to build services, CLIs and tested automation • Working knowledge of Kubernetes, containers, Helm and GitOps workflows • Strong Linux skills • Deep knowledge of AWS, GCP or Azure; AWS preferred • Experience with LLM application patterns including prompt and context management, retrieval, tool use, structured output and evaluation • Ability to work independently inside a customer environment and communicate progress clearly • Three references required

🏖️ Benefits

• Remote work environment • Occasional US travel opportunities for customer workshops, platform bring-up and go-live • Pre-sales support, internal platform work and knowledge-sharing time • Full-time position

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