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HavocAI

AI Systems Engineer - Agentic Autonomy

Posted 3 Days Ago
In-Office or Remote
2 Locations
140K-180K Annually
Mid level
In-Office or Remote
2 Locations
140K-180K Annually
Mid level
The AI Systems Engineer will design AI-powered components for mission systems, integrate LLMs into autonomy frameworks, optimize AI system performance, and lead collaboration across engineering disciplines.
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About Us:

Collaborative autonomy is how self-tasking teams of machines will solve hard human problems, and HavocAI is an unquestioned leader in collaborative autonomy. We set the standard for autonomous surface vessels for a wide range of defense and commercial maritime missions. Success requires us to grow quickly, and we’re looking for teammates who are passionate about solving hard problems, about pushing the envelope, and about preventing conflict and saving lives. Ambition is welcome to apply within.

About the Role:

We are seeking an AI Systems Engineer with deep expertise in large language models (LLMs), agentic AI architectures, and integrating advanced AI models into production-grade robotic or mission systems. You will lead the design and deployment of AI-powered components that enhance human–machine teaming, mission planning, situational understanding, and autonomy decision-making.

This role sits at the intersection of ML engineering, systems engineering, autonomy, and product design. You will define how LLMs and multi-agent AI systems interface with autonomy stacks, sensor pipelines, simulation tools, and operations software across multiple product lines.

Key Responsibilities and Requirements:
  • Lead the design and development of LLM-powered software modules for mission reasoning, planning, operator interaction, and autonomous decision support.

  • Integrate LLMs and agentic systems into HavocAI’s autonomy architecture, including ROS/ROS2 systems, planning engines, and mission software.

  • Build multi-agent, tool-using AI systems that interact with perception data, mission databases, simulation systems, and operator inputs.

  • Develop APIs, wrappers, and orchestration layers enabling LLMs to interface safely with embedded, cloud, and edge compute environments.

  • Optimize LLM inference pipelines for performance, latency, and reliability in field-deployed systems.

  • Evaluate model behavior, perform safety testing, and develop guardrails for mission-critical use cases.

  • Collaborate with autonomy, embedded, simulation, and full-stack teams to define requirements and ensure robust system-level integration.

  • Guide strategic decisions on model selection, fine-tuning approaches, safety frameworks, and long-term AI architecture.

  • Contribute to field testing, operator evaluations, and iterative deployment cycles for AI-augmented autonomy systems.

Qualifications:
  • Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, Robotics, or a related field.

  • Deep hands-on experience building with LLMs and multi-agent/agentic AI frameworks.

  • Strong software engineering background in modern ML frameworks, cloud orchestration, and API development.

  • Experience integrating AI systems into larger software architectures or robotics/autonomy workflows.

  • Understanding of RAG pipelines, tool-use frameworks, LLM function-calling, memory systems, and agent orchestration.

  • Experience with safety evaluation, model alignment, or mission-critical AI system validation.

  • Ability to lead system-level design discussions and coordinate across multiple engineering disciplines.

  • Must be a U.S. Citizen and eligible to obtain a Secret Clearance.

Preferred Skills:
  • Experience with autonomy stacks (ROS/ROS2, PX4, mission planning engines).

  • Background in simulation, decision-theoretic planning, or multi-agent coordination.

  • Experience training or fine-tuning LLMs, building embeddings pipelines, or deploying models on-premise.

  • Knowledge of defense, maritime, or dual-use tech environments.

  • Familiarity with distributed compute systems, GPU optimization, or edge inferencing.

  • Prior experience shaping AI product strategy or leading ML/AI engineering teams.

Benefits:
  • 100% Employer paid Health, Dental and Vision Insurance for you and your families

  • Life Insurance

  • Ability to participate in the companies 401k program

  • 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


Our Values:
  • Innovation: We are driven to break new ground. Every day presents an opportunity to challenge the status quo, think boldly, and deliver advanced solutions that transform the future of defense technology.

  • Integrity: We hold ourselves to the highest ethical standards, ensuring transparency, accountability, and trust in all our actions and partnerships.

  • Mission-Driven: We are focused on achieving impactful outcomes that align with our core mission—protecting lives through innovation.

  • Forward-Leaning: We continuously seek out new opportunities and remain at the forefront of technological advancements. We embrace change and anticipate the challenges of tomorrow with confidence and creativity.

  • Ownership of All Tasks: At HavocAI, no problem is too complex or too trivial. We believe that greatness comes from tackling the hardest challenges, but also in handling the smallest, sometimes thankless, tasks with the same level of commitment and care.

  • Servant Leadership: We lead by serving others, whether it’s supporting our employees, partners, or the broader community. Empowering those around us is key to achieving long-term success and making a lasting impact.

HavocAI is an Equal Opportunity Employer and is committed to creating an inclusive and diverse workplace. We welcome applicants from all backgrounds and do not discriminate based on race, color, religion, gender, sexual orientation, age, national origin, disability, veteran status, or any other legally protected status.

Top Skills

Agentic Ai Architectures
APIs
Cloud Orchestration
Large Language Models
Llms
Ros
Ros2

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