Director of Engineering

Position SummaryCircadence is seeking a Director of Engineering with deep AI expertise to serve as the technical leader across our commercial product suite. This role is both hands-on and strategic: you will be the primary engineering owner of RangeGPT, while also providing cross-product technical direction for other commrecial products, Range Conductor and Project Ares, in close partnership with the CTO.RangeGPT is Circadence's flagship AI platform, combining LLM-driven reasoning, LangGraph orchestration, and real-time infrastructure automation to enable cybersecurity professionals to design and deploy realistic training environments. As Director of Engineering, you will lead the team building and scaling this platform, while contributing meaningfully to the architectural coherence of the broader product portfolio.You will own people management across the engineering organization: hiring, performance reviews, career development, and team structure. This is a role for an engineering leader who is equally comfortable in architectural design sessions, 1:1s with engineers, and executive strategy discussions.About Circadence CorporationCircadence is a premier provider of cyber range solutions, specializing in the creation, implementation, and management of tailored enterprise frameworks. Focused on cybersecurity infrastructure, simulation, and education, Circadence excels across academic, enterprise, and government use cases.Our approach combines gamification and active-learning models with scalable, cloud-based platforms aligned to the NIST/NICE Cybersecurity Framework. Our product suite includes Range Conductor (cyber range orchestration), ProjectAres (gamified training), and RangeGPT (AI-driven range design and analysis).Key Responsibilities:RangeGPT: AI Platform LeadershipOwn the technical roadmap and architectural direction for RangeGPT, including LLM workflow design, LangGraph orchestration patterns, and infrastructure agent integration.Architect and evolve RangeGPT's agent harness: the orchestration infrastructure surrounding the LLM core, spanning context management, tool and API integrations, memory systems, guardrails, and multi-agent coordination.Lead context engineering efforts across the platform: designing prompt architecture, retrieval strategies, structured context assembly, and dynamic context windowing to maximize model performance and reliability.Lead and grow the RangeGPT engineering team, setting technical standards, reviewing designs, and driving delivery.Oversee development of backend systems, scalable APIs, and agentic workflows that connect AI reasoning layers with cyber range infrastructure.Ensure platform reliability, observability, and performance at scale across data-intensive and latency-sensitive workloads.Client Engagement and Technical SolutioningServe as a technical lead in client-facing engagements: requirements gathering sessions, solution scoping, and translating operational cybersecurity needs into RangeGPT platform capabilities.Deliver technical demos and proof-of-concept presentations to prospective and existing clients, including government and enterprise audiences.Partner with business development and account teams to support pre-sales technical discovery, proposal development, and contract scoping.Maintain ongoing client relationships through the delivery lifecycle, acting as a technical point of contact for escalations, feature requests, and integration questions.Synthesize client feedback into actionable engineering priorities and roadmap inputs in collaboration with product leadership.Cross-ProductTechnical DirectionPartner with the CTO to define and maintain the technical strategy across the full Circadence product suite: Range Conductor, Project Ares, and RangeGPT.Identify integration opportunities and shared infrastructure across products, reducing duplication and increasing platform coherence.Provide technical review and architectural guidance on Range Conductor and Project Ares engineering decisions, escalating tradeoffs and risks to the CTO as needed.Stay current on the AI/ML and cybersecurity tooling landscape to inform strategic product and build/buy decisions.People Management and Organizational DevelopmentManage the full engineering organization: hiring, onboarding, goal setting, performance reviews, and career development.Build and maintain a high-performance engineering culture grounded in technical rigor, ownership, and continuous improvement.Define team structure and staffing plans aligned to product roadmap priorities.Act as a technical mentor and escalation point for engineers across the organization.Research, Innovation, and DeliveryDrive research and prototyping efforts for novel ML algorithms, agentic reasoning patterns, and predictive modeling capabilities within the platform.Champion engineering best practices: CI/CD, MLOps, observability, testing, and documentation.Collaborate cross-functionally with product, sales,and customer successto align engineering execution with business outcomes.Lead performance benchmarking and capacity planning for AI systems handling complex data volumes and real-time processing requirements.Qualifications:EducationBachelor's degree in computer science, Engineering, or a related field required.Master's or Ph.D. is strongly preferred, particularly in AI, machine learning, or a related technical discipline.Experience7+ years of engineering experience, with at least 3 years in a senior technical leadership or management role.Demonstrated experience leading teams delivering AI or ML-powered production systems.Experience in cybersecurity, defense, or simulation technology space is a significant plus.Demonstrated experience in client-facing technical roles: requirements gathering, solution scoping, demos, and delivery-phase client engagement, ideally with government or enterprise customers.Track record of successfully partnering with executive leadership on technical strategy.Technical ExpertiseStrong command of LLM application architecture, including prompt engineering, retrieval-augmented generation, and agentic orchestration frameworks (e.g., LangGraph, LangChain).Hands-on experience designing and building agent harnesses: the orchestration layer around LLMs encompassing context pipelines, tool registries, memory architectures, guardrails, and multi-agent coordination patterns.Deep familiarity with context engineering: structured prompt design, dynamic context assembly, retrieval integration, and context window management strategies for production agentic systems.Proficiency with cloud infrastructure, distributed systems, and API design.Hands-on familiarity with ML Ops tooling, observability platforms, and deployment pipelines.Working knowledge of machine learning fundamentals, including supervised/unsupervised learning, deep learning, and model evaluation.Leadership and Interpersonal SkillsProven ability to manage, develop, and retain engineering talent across multiple teams.Strong analytical and problem-solving skills at the intersection of AI, infrastructure, and product.Excellent communication skills: ability to translate technical complexity for executive and non-technical audiences.Comfort operating in a fast-moving, resource-conscious environment with shifting priorities.Compensation and BenefitsCompetitive salary commensurate with experience.Medical, Vision and Dental Insurance.401(k) plan with companymatching.Life and Accidental Death and Dismemberment Insurance.Flexible SpendingAccount (FSA) or Health SavingsAccount (HSA) (with a high-deductible plan).Critical Illness and Accident Insurance.Flexible Paid Time Off (PTO) and Company recognizes all Federal Holidays.Circadence Corporation is proud to be an equal opportunity employer.https://www.eeoc.gov/know-your-rights-workplace-discrimination-illegal