The Role Serves as PDW's senior AI/ML technical leader, defining enterprise AI strategy, architecture, standards, and roadmap while building production systems. Develops RAG solutions, AI agents, orchestration platforms, evaluation frameworks, APIs, data pipelines, and MLOps infrastructure. Leads AI security and governance, optimizes models across cloud and GPU environments, partners across engineering and business teams, and mentors teams adopting AI technologies. Requires extensive hands-on experience with generative AI, production ML systems, secure architecture, and enterprise deployment. Summary Generated by Built In Performance Drone Works (PDW) is building the next generation of tactical robotic systems used across defense, national security, and public safety missions. We are building a new center of engineering excellence to design our new category of tactical robotic systems and the industrial capacity to deliver them, bringing decisive airpower into the hands of every operator. We are not here to make promises; we are here to deliver real systems with real capabilities for real missions. You will join a team of operators, engineers, and builders who solve hard problems with humility and focus. We design and produce multi-mission aerial systems that operators trust to perform in real-world conditions, reliably, repeatedly, and at scale. Our approach is grounded in operator-centered design, rapid iteration from field use, and U.S.-based manufacturing. We operate by a clear set of values: Mission First, Aim Farther, Own It, Win Together. This is how we build advantage and how we help protect our service members, our communities, and our country. Now, we're entering a new phase of growth and are looking for a Senior AI/ML Engineer to serve as PDW's senior technical leader for enterprise AI—helping define our AI strategy, architecture, and technical roadmap while remaining hands-on in building and scaling the capabilities that put that vision into production. What You'll Do Serve as PDW's senior technical authority for enterprise AI/ML, partnering with technology leadership to shape the AI strategy, architecture, technical roadmap, engineering standards, and investment priorities—and taking hands-on ownership of turning that direction into working capabilities. Design and implement AI orchestration and control capabilities including model routing, authentication and authorization, policy enforcement, observability, usage tracking, cost management, and auditability. Build production retrieval-augmented generation (RAG) solutions, including ingestion pipelines, chunking, embeddings, vector search, retrieval, reranking, and generation across structured and unstructured enterprise data. Develop AI agents and agentic workflows that securely interact with enterprise applications, APIs, data sources, and business processes while respecting underlying identity and authorization boundaries. Partner with Engineering, Manufacturing, IT, Cybersecurity, and business teams to identify high-value AI opportunities, rapidly prototype solutions, evaluate technical feasibility, and transition successful concepts into production. Develop repeatable model evaluation and benchmarking frameworks to compare models and architectures based on quality, accuracy, latency, reliability, security, and cost using PDW-specific workloads. Design, build, and operate production AI/ML applications, APIs, data pipelines, evaluation frameworks, and supporting infrastructure using modern software engineering, CI/CD, and MLOps practices. Evaluate and optimize AI workloads across SaaS, API, cloud, GPU, and internally hosted infrastructure, including opportunities for model optimization, fine-tuning, quantization, and accelerated inference. Implement technical controls for AI security and governance, including data protection, access control, model and provider restrictions, guardrails, validation, human oversight, and protection against threats such as prompt injection and data leakage. Establish PDW's AI engineering discipline, including reusable patterns, reference architectures, development standards, documentation, and technical governance; mentor engineers and teams adopting AI; and continuously evaluate emerging technologies to recommend how PDW's AI strategy and architecture should evolve. Requirements 7+ years of progressive experience in software engineering, machine learning engineering, data engineering, AI engineering, or a related technical discipline, with significant recent hands-on experience developing AI/ML systems. Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Engineering, or a related STEM discipline, or equivalent combination of education and relevant professional experience. Advanced proficiency in Python and demonstrated experience building production-quality software, services, APIs, data pipelines, and distributed systems. Hands-on experience with modern AI/ML frameworks such as PyTorch, TensorFlow, or JAX, with a strong understanding of machine learning fundamentals, neural networks, transformers, embeddings, and modern generative AI architectures. Demonstrated experience building production applications using large language models and foundation models, including prompt engineering, structured generation, tool/function calling, and model APIs. Demonstrated experience designing and implementing RAG architectures, including document ingestion, embeddings, vector databases or search, retrieval strategies, reranking, context management, and evaluation. Experience building AI agents, tool-enabled models, workflow orchestration, or other agentic systems that interact with applications, APIs, and enterprise data. Experience deploying and operating AI/ML systems in production, including automated testing, CI/CD, containers, monitoring, evaluation, observability, performance optimization, and MLOps practices. Strong understanding of secure application architecture, identity and access control, data protection, and the security considerations associated with enterprise AI systems. Demonstrated ability to independently translate ambiguous business or technical problems into architectures and working solutions, troubleshoot complex systems, communicate effectively with technical and non-technical stakeholders, and take solutions from exploration through production. Must have the ability to obtain and maintain a U.S. Security Clearance. Preferred Experience building enterprise AI platforms, AI gateways, model-routing architectures, or multi-model environments using multiple commercial and/or open-source AI ecosystems. Experience deploying and optimizing open-source AI models on GPU infrastructure, including model serving, inference optimization, quantization, and/or distributed inference, with the ability to evaluate the performance, cost, and operational tradeoffs of internally hosted versus API-based models. Experience developing AI/ML systems within aerospace, defense, robotics, manufacturing, or another highly technical or regulated environment, including working with sensitive or export-controlled information. Physical Requirements The physical demands described here are representative of those that must be met to successfully perform the essential functions of the job. Ability to sit, stand, bend, reach, climb, and move about regularly throughout the day and lift / carry up to 25 pounds. Must have manual dexterity to operate standard office and computer equipment. Must be physically capable of occasionally assisting with the setup, movement, and installation of computer, networking, development, or GPU computing equipment. Work Environment This is a hybrid position with regular on-site presence and typically operates in a standard office environment and within PDW facilities that house engineering and manufacturing operations. This role requires the use of standard office and computing equipment and close cross-departmental collaboration with both independent and team-based responsibilities. Occasional travel between PDW sites, partner locations, industry events, or other business locations may be required. Standard work hours are PDW's core business hours, with availability outside those hours as needed for significant production AI platform incidents or operational priorities. Benefits PDW values our team, and we offer a compensation package reflective of your experience and capabilities.

Benefits include:

Comprehensive BCBS medical, dental, and vision coverage; 80% sponsored by the company. Safe Harbor 401(K) with company match. Paid Parental Leave. On-site gym at our Huntsville, AL and Denver, CO locations. Employer provided life insurance. Robust Employee Assistance Program (EAP). A work environment that encourages teamwork and innovation. Competitive salary, generous paid time off (PTO), and flexible leave options. EEO Statement PDW is an equal opportunity employer that upholds all federal and state non-discrimination laws. We ensure a fair and unbiased evaluation for employment for all qualified candidates regardless of race, color, religion, age, sex, sexual orientation, gender identity, national origin, marital status, medical condition, disability, genetic information, veteran status, or any other characteristic protected by law. Read Full Description Skills Required 7+ years of progressive experience in software engineering, machine learning engineering, data engineering, AI engineering, or a related technical discipline, including significant recent hands-on AI/ML systems experience. Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Engineering, or a related STEM discipline, or equivalent education and relevant professional experience. Advanced proficiency in Python and experience building production-quality software, services, APIs, data pipelines, and distributed systems. Hands-on experience with PyTorch, TensorFlow, or JAX and strong knowledge of machine learning fundamentals, neural networks, transformers, embeddings, and generative AI architectures. Experience building production applications with large language models and foundation models, including prompt engineering, structured generation, tool or function calling, and model APIs. Experience designing and implementing RAG architectures, including ingestion, embeddings, vector search, retrieval, reranking, context management, and evaluation. Experience building AI agents, tool-enabled models, workflow orchestration, or agentic systems interacting with applications, APIs, and enterprise data. Experience deploying and operating production AI/ML systems, including testing, CI/CD, containers, monitoring, evaluation, observability, performance optimization, and MLOps. Strong understanding of secure application architecture, identity and access control, data protection, and enterprise AI security considerations. Ability to translate ambiguous problems into architectures and working solutions, troubleshoot complex systems, communicate with technical and non-technical stakeholders, and take solutions through production. Ability to obtain and maintain a U.S. security clearance. Experience building enterprise AI platforms, AI gateways, model-routing architectures, or multi-model environments. Experience deploying and optimizing open-source AI models on GPU infrastructure, including model serving, inference optimization, quantization, or distributed inference. Experience developing AI/ML systems in aerospace, defense, robotics, manufacturing, or other highly technical or regulated environments. View all jobs at Performance Drone Works View Performance Drone Works Profile Report Job