Jobs at Shield AI

Partners with business stakeholders and AI leadership to identify and evaluate workplace AI use cases, quantify business impact, develop buy-versus-build recommendations, and track adoption, performance, and ROI. The role analyzes workflows and operational data, creates baselines, dashboards, business cases, vendor comparisons, and executive-ready recommendations to guide AI implementation and adoption strategies.

Administers and optimizes Shield AI’s talent acquisition and people technology ecosystem, including Ashby ATS/CRM and related HR platforms. Owns configuration, integrations, permissions, data governance, reporting, vendor management, release management, UAT, and compliance controls. Partners with People Technology and cross-functional stakeholders on technology roadmaps and system design. Initially an individual contributor, the role is expected to grow into a player-coach position leading a TA and PX systems team.

Leads strategic capture, sales, and customer engagement for X-BAT and advanced systems supporting U.S. Air Force markets. Shapes solicitations, guides acquisition-office interactions, builds program-office and industry relationships, influences requirements and policy, and drives teams toward high-value, multi-year Air Force contract wins. Owns the business development lifecycle for emerging aerospace and defense technologies.

Lead Shield AI’s capture and strategic sales efforts for X-BAT and advanced systems supporting USMC and Department of the Navy customers. Shape acquisition opportunities, guide solicitation responses, build program-office and industry relationships, influence requirements, and drive multi-year contract wins. The role requires deep DoN/USMC acquisition expertise, defense sales experience, technical credibility, leadership skills, an active Secret clearance, and DAWIA Program Manager Advanced certification.

Lead operational reliability and platform enablement for Databricks: build monitoring, CI/CD, deployment standards, compute and job policies, observability, runbooks, and governance to support secure, cost-aware, production data workloads across regulated environments. Mentor engineers and align platform with cloud/infrastructure and compliance requirements.

Leads enterprise strategy and operational execution across aerospace, defense, AI, hardware, software, and international growth. Responsibilities include strategic planning, portfolio tradeoff analysis, market sizing, competitive analysis, financial modeling, capital allocation, business case development, KPI tracking, performance reviews, root-cause analysis, and cross-functional execution. The role requires influencing senior stakeholders and translating strategic priorities into measurable outcomes.

Lead multi-year strategic planning and annual operating cycles, evaluate portfolio tradeoffs, build financial models for capital allocation, and translate strategy into cross-functional execution plans with KPIs. Conduct market sizing, competitive analysis, scenario modeling, and track performance through operating cadences to identify bottlenecks and recommend solutions.

Drives business development and specialist sales for Aechelon simulation products across defense, aviation, and synthetic training markets. Builds customer and partner relationships, identifies and qualifies opportunities, manages forecasts and pipelines, supports demonstrations, proposals, quotations, and capture efforts, and translates simulation capabilities into mission-relevant customer value. Collaborates with sales, product, engineering, programs, contracts, marketing, and finance teams to advance complex technology pursuits and maintain accurate internal alignment.

Develop state estimation and navigation algorithms for autonomous systems operating in GPS-denied environments. Build production-grade C++ software for embedded Linux robotic platforms, create modeling and simulation tools, and implement comprehensive testing and validation. Collaborate on roadmap planning and agile execution while improving benchmarking and performance-analysis pipelines. The role requires professional C++ expertise, state estimation algorithm experience, sensor-fusion familiarity, and the ability to deploy reliable autonomy software.

Develop deep learning and 3D computer vision models for state estimation, visual navigation, localization, depth, correspondence, and pose estimation. Own data preparation, training, evaluation, benchmarking, and reproducible workflows. Integrate learned measurements into VIO and terrain-relative navigation systems, optimize models for onboard compute, and collaborate with deployment, software, systems, and flight-test teams to deliver production-ready Hivemind SDK components.

Leads Shield AI’s Enterprise Data delivery organization, managing data engineering, analytics engineering, domain enablement, and governance teams. Translates enterprise data strategy into sequenced roadmaps, manages priorities, capacity, dependencies, risks, and stakeholder expectations, and ensures production-ready, governed data products. Partners with architecture, platform engineering, security, and business leaders on technical tradeoffs, data quality, lineage, reliability, and investment priorities. Also owns hiring, coaching, performance development, delivery metrics, and continuous improvement of the data operating model.

Build and lead a scalable application security and secure SDLC program across engineering teams. Establish policies, standards, tooling, vulnerability management, threat modeling, developer enablement, security champions, software supply-chain controls, and executive reporting. Partner with development, platform, DevOps, product, and leadership teams to integrate security into CI/CD, source control, build, release, and deployment workflows while supporting audits, advisories, incident response, and regulatory requirements.

Lead systems engineering for a next-generation unmanned aircraft system. Responsibilities include defining system architecture, behaviors, requirements, interfaces, fault responses, and traceability; integrating avionics, autonomy, propulsion, sensors, and mission systems; conducting MBSE modeling, trade studies, safety analyses, flight testing, and performance validation; and coordinating cross-functional teams, DoD stakeholders, and government partners through development and operational deployment.

Deploy and integrate Shield AIs Hivemind autonomy software with customers worldwide. Provide on-site technical support, training, debugging, and documentation. Collaborate with sales and product engineering to support pre- and post-sales activities and improve autonomy products.

Lead product definition, roadmap, and adoption for the CTOs agentic AI portfolio. Translate strategy into requirements, KPIs, and milestones; run discovery, prioritize backlogs, instrument usage, and shepherd incubation-to-handoff for AI/dev platforms and foundation-model tooling.

Lead design and implement production React/TypeScript interfaces for agentic AI products. Prototype and ship working front-end code, design interaction patterns for LLM-driven systems, run user research, build reusable component patterns, instrument usage, and collaborate with product teams to land designs into production.

Lead systems engineering for Hivemind-based autonomy products: define and manage requirements, develop system architectures and trade studies, coordinate hardware/software interfaces, support integration/verification/validation and testing, and identify and mitigate technical risks across the system lifecycle.

Lead design and prototyping of generative AI experiences for autonomy development; drive UX for Hivemind products; perform user research, collaborate with CTO and product leads, and deliver reference implementations and integrations across full-stack web and edge systems.

Drive supplier development for electronic assemblies (PCBA/SMT): audit processes, resolve manufacturing defects, perform root-cause analysis and corrective actions, enforce IPC/J-STD standards, support NPI, monitor supplier performance, and mitigate supply chain risk with frequent supplier travel.

Lead supplier development for machined parts: audit and improve supplier processes, perform on-site quality investigations, support NPI, provide technical guidance on specifications and manufacturing, monitor supplier performance, and mitigate supply chain risks to enable scalable aerospace production.