AI Infrastructure Engineer – Agents, ML Systems

🕒 August 5

🇺🇸 United States – Remote

💵 $175k - $200k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

👷 Infrastructure Engineer

👻 Ghost score 20%

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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HavocAI

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2024

📦 Logistics

🏭 Manufacturing

🎖️ Defense

💰 Seed Round on 2024-09

Logistics • Manufacturing • Defense

HavocAI is a developer of collaborative autonomy for maritime operations, offering a modular software and vehicle stack that enables fleets of autonomous maritime systems to perform contested logistics, sensor fusion and tracking, domain awareness, and escort-and-engage missions. Their product suite includes onboard autonomy (HAVOC OS), scalable communications (HAVOC CLOUD), and a handheld operator interface (HAVOC CONTROL), marketed as a single solution for theater-scaled security and rapid deployment. HavocAI emphasizes real-time, team-led autonomous solutions that run across diverse environments and supports both hardware (autonomous vessels) and software deployment.

📋 Description

• Build internal AI infrastructure connecting LLMs and AI agents with internal tools, APIs, data sources, data lakes, telemetry stores, simulation tools, code repositories, documentation systems, logs, and engineering workflows. • Develop and maintain agentic AI systems for task automation, data analysis, engineering support, simulation workflows, and internal productivity. • Build tool integration and connector infrastructure for AI agents, including MCP and other emerging tool-use standards. • Create pipelines for retrieval, RAG, context management, document processing, embeddings, and internal knowledge search. • Support ML infrastructure workflows including data preparation, dataset curation, experiment tracking, model evaluation, fine-tuning support, and model deployment. • Build evaluation frameworks for agent performance, tool-use reliability, task success, model quality, regression testing, and failure analysis. • Develop observability, logging, tracing, auditability, monitoring, and debugging tools for AI agents, model calls, MCP tools, and ML pipelines. • Partner with Autonomy, Software, Data, Simulation, Product, and Operations teams to identify AI use cases and build reliable internal tools. • Secure agentic AI systems using least-privilege access, sandboxed execution, prompt-injection mitigation, secrets management, human approvals, and safe handling of sensitive and defense data. • Maintain documentation, reusable examples, templates, and best practices for safe AI-tool adoption.

🎯 Requirements

• Bachelor's degree in Computer Science, Engineering, Machine Learning, Data Science, Applied Mathematics, or a related technical field. • 3+ years of experience in software engineering, infrastructure engineering, ML infrastructure, backend systems, data engineering, developer tools, or related technical roles. • Strong programming experience in Python, TypeScript, Go, C++, or similar languages. • Experience building production software systems, APIs, services, data pipelines, or internal platforms. • Experience with, or strong interest in, LLM applications, AI agents, tool-using systems, RAG pipelines, or AI developer tools. • Familiarity with embeddings, vector search, prompt management, evaluation, model serving, fine-tuning, or MLOps. • Ability to integrate APIs, databases, object stores, documents, logs, internal tools, and structured or unstructured data sources. • Strong understanding of reliability, observability, testing, and maintainability. • Strong grounding in securing AI and agentic systems, including least-privilege tool access, prompt-injection and misuse mitigation, secrets management, and safe handling of sensitive data. • Ability to work across Software, Data, ML, Infrastructure, and Product teams. • Strong debugging skills and comfort working with complex distributed systems. • U.S. citizenship and ability to obtain and maintain a security clearance. • Preferred: experience with MCP, AI tooling, vector databases, embeddings, retrieval, RAG, fine-tuning, Kubernetes, Docker, Ray, Airflow, Dagster, MLflow, Weights & Biases, Kafka, Postgres, S3-compatible storage, internal platforms, workflow automation, human-in-the-loop systems, engineering integrations, autonomy, robotics, simulation, telemetry, perception, defense technology, or secure AI systems. • Active or prior security clearance preferred.

🏖️ Benefits

• 100% Employer paid Health, Dental and Vision Insurance for you and your families • Life Insurance (Employer Paid) • Ability to participate in the companies 401k program (Matching) • Unlimited PTO policy with an enforced 2 week minimum • Equity Package • Work / Home Office Stipend • Global Entry • 16 Week Paid Parental Leave • Monthly Health and Wellness Stipend • Bonus offered (compensation summary) • Remote work arrangement