Senior AI Engineer

Job not on LinkedIn

🕒 2 days ago

🔔 Pennsylvania, Virginia – Remote

🔔 Pennsylvania – Remote ⚔️ Virginia – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.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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Air

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2017

☁️ SaaS

📱 Media

📣 Marketing

💰 $35M Series B - Air on 2025-01

SaaS • Media • Marketing

Air is an AI-native creative operations and digital asset management (DAM) platform that helps teams organize, find, edit, approve, and multiply creative assets at scale. It combines conversational search, auto-tagging/creative intelligence, AI design and bulk editing (Canvas), reviews & approvals, workflow and brand management, integrations and enterprise security to centralize creative libraries and accelerate content production across channels. Air targets marketing, media, agencies, retail/e‑commerce and product teams seeking faster creative workflows and data-driven asset performance.

📋 Description

• Design, build, and improve production agentic AI systems for complex real-world problems • Develop agent architectures for reasoning, planning, tool use, context management, memory, and multi-step task execution • Build secure tools and capabilities for agents to interact with data, APIs, code, and external systems • Develop model and inference infrastructure for commercial and open-weight language models • Evaluate models, inference techniques, and emerging AI capabilities for production use • Build automated evaluation frameworks, datasets, benchmarks, and methodologies for agentic workflows • Improve agent performance through prompt and context engineering, model selection, tool design, inference strategies, and architecture • Build scalable APIs, services, and infrastructure for agent execution and AI-powered product experiences • Design asynchronous and long-running agent workflow systems • Build safe execution infrastructure for agent-generated code and computational workloads • Improve observability using logging, metrics, distributed tracing, dashboards, and alerting • Investigate failures across models, agents, application code, and distributed infrastructure • Optimize systems for latency, throughput, reliability, and infrastructure cost • Translate AI research and emerging techniques into production improvements • Collaborate with product, platform, security, and domain teams to move AI capabilities from experimentation to production

🎯 Requirements

• U.S. Citizenship is required • 5+ years of experience building production software, AI/ML systems, distributed systems, or similar technical systems • Deep experience designing, building, and operating production AI agents or agent platforms • Experience developing core agent infrastructure, including agent runtimes, tool execution, context management, memory, orchestration, or related platform capabilities • Strong understanding of state-of-the-art agent architectures and engineering tradeoffs for reliable, production-grade agentic systems • Experience designing agents that use tools, reason across multi-step tasks, interact with external systems, and operate over long-running or complex workflows • Experience building agent evaluation systems, including task-level evaluations, behavioral evaluations, regression testing, and production quality measurement • Strong understanding of modern LLM systems, including model inference, context engineering, structured outputs, tool calling, retrieval, model selection, and agent-performance techniques • Ability to evaluate emerging models, research, and agent techniques and translate them into production systems • Strong Python programming experience and production-quality software development • Experience designing scalable APIs, services, asynchronous systems, and event-driven architectures • Experience operating production services using Kubernetes and AWS, GCP, or Azure • Strong understanding of distributed systems, containers, service orchestration, networking, storage, and scalable architectures • Ability to debug complex failures across model behavior, agent execution, application code, and production infrastructure • Ability to move between research and engineering, prototype ideas, evaluate them rigorously, and productionize successful approaches • Comfortable working in a rapidly evolving field • Desired: current U.S. security clearance or ability to obtain one with sponsorship • Desired: startup or entrepreneurial environment experience • Desired: secure code execution environments or AI-agent sandboxes • Desired: multi-agent architectures, agent-to-agent communication, or distributed agent execution • Desired: fine-tuning, post-training, reinforcement learning, or synthetic data generation • Desired: AI observability, tracing, and debugging infrastructure • Desired: inference latency, throughput, GPU utilization, or model-serving cost optimization • Desired: AI security, adversarial testing, or securing agentic systems • Desired: government, defense, or mission-critical environment experience

🏖️ Benefits

• Equal Opportunity Employer • Security clearance sponsorship available for qualified candidates who can obtain one