• Build and deliver AI solutions: Take ownership of developing high-performance AI features to help users detect, triage, and resolve incidents using observability data and tools. • Rapid experimentation and iteration: Implement a highly iterative process where you quickly prototype, test, and validate with real users, including shipping and evolving LLM- or agent-powered workflows for incident lifecycle management and automated analysis tasks. • Collaborate cross-functionally: Work with data analysts, product managers, and designers to shape AI-driven product features, including integration of agentic components with internal tools, alerting systems, runbooks, and developer workflows. • Utilize AI tools effectively: Use AI and automation tools to enhance both product functionality and your own development workflows. • Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. • Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows.

Title: Staff Applied AI Engineer Location: Westminster, CO Job Description: Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what’s happening now and shape what’s coming next. Vantor is a place for problem solvers, changemakers, and go-getters—where people are working together to help our customers see the world differently, and in doing so, be seen differently. Come be part of a mission, not just a job, where you can: Shape your own future, build the next big thing, and change the world. To be eligible for this position, you must be a U.S. Person, defined as a U.S. citizen, permanent resident, Asylee, or Refugee. Export Control/ITAR: Certain roles may be subject to U.S. export control laws, requiring U.S. person status as defined by 8 U.S.C. 1324b(a)(3). Please review the job details below. We are seeking a hands-on Staff-level Applied AI Engineer to build the next generation of decision intelligence within our mission planning systems. This role focuses on learning from historical mission data, quantifying economic outcomes, and improving planning decisions through optimization and machine learning. You will operate as a roving specialist across our engineering organization, working at the intersection of data, algorithms, and operational systems to unlock measurable business impact. This is not a generic AI role. You will be solving real-world constrained optimization problems with direct revenue implications. The next generation MPS system doesn’t just automate—it needs to both think and act. With AI built in, MPS will function as a digital operator capable of scheduling tasks on specific sensors and autonomously managing and optimizing constellations, while keeping human operators in the loop with auditable controls. Cybersecurity must be engineered in—not bolted on. The system will align to zero trust principles and modern DevSecOps practices to accelerate accreditation and deployment across missions. An open architecture and integrated data layer will enable secure collaboration with allies without sacrificing security. This system must be cloud-native and capable of operating from anywhere. With remote access and seamless integration across terrestrial and space-based networks, operators will compress satellite tasking cycles from days to minutes while maintaining secure operations (potentially) globally. What You’ll Do • Develop models to attribute revenue to individual collection plans • Build counterfactual and simulation frameworks to evaluate alternative strategies • Design decision-support systems used daily by mission planners • Apply optimization, reinforcement learning, and heuristic approaches • Map system complexity and identify efficiency improvements • Rapidly prototype solutions using AI-assisted development tools • Collaborate across engineering, data, and product teams · Engineer AI-driven capabilities that enable MPS to act as an autonomous or semi-autonomous operator, balancing automation with human-in-the-loop control · Design and build systems aligned to zero trust and DevSecOps principles, ensuring security is foundational—not an afterthought · Contribute to open architecture and integrated data layer strategies that enable secure collaboration with partners and allied systems · Build and deploy cloud-native solutions that enable remote mission operations and dramatically reduce planning cycle times What Success Looks Like (12–18 Months) • A decision-support system is actively used by planners in daily operations · Vantor can quantify revenue at the level of individual collection plans · Teams can evaluate alternative planning strategies with measurable economic outcomes · Early-stage learning systems (optimization / RL) are improving planning performance over time Minimum Qualifications • 5+ years building data-driven or ML-powered systems • Strong Python or similar programming skills • Experience with optimization, simulation, or decision systems • Ability to work in complex problem spaces • U.S. Citizenship required · Bachelor’s or Master’s degree in Computer Science, Applied Mathematics, Operations Research, Engineering, or a related field Preferred Qualifications • Experience with operations research or reinforcement learning • Background in decision science or economics • Experience with simulation environments • Familiarity with geospatial or satellite systems • Experience in mission-critical or ITAR environments Pay Transparency: In support of pay transparency at Vantor, we disclose salary ranges on all U.S. job postings. The successful candidate’s starting pay will fall within the salary range provided below and is determined based on job-related factors, including, but not limited to, the experience, qualifications, knowledge, skills, geographic work location, and market conditions. Candidates with the minimum necessary experience, qualifications, knowledge, and skillsets for the position should not expect to receive the upper end of the pay range. ● The base pay for this position within Colorado is: $124,000.00 - $206,000.00 annually. For all other states, we use geographic cost of labor as an input to develop market-driven ranges for our roles, and as such, each location where we hire may have a different range. Benefits: Vantor offers a competitive total rewards package that goes beyond the standard, including a robust 401(k) with company match, mental health resources, and unique perks like student loan repayment assistance, adoption reimbursement and pet insurance to support all aspects of your life. Additionally, this position is incentive eligible with a target based on contribution, company performance, and/or individual results achieved; the specific incentive plan and target amount will be determined based on the role and breadth of contributions. The application window is three days from the date the job is posted and will remain posted until a qualified candidate has been identified for hire. If the job is reposted regardless of reason, it will remain posted three days from the date the job is reposted and will remain reposted until a qualified candidate has been identified for hire. The date of posting can be found on Vantor's Career page at the top of each job posting. To apply, submit your application via Vantor's Career page. EEO Policy: Vantor is an equal opportunity employer committed to an inclusive workplace. We believe in fostering an environment where all team members feel respected, valued, and encouraged to share their ideas. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability, protected veteran status, age, or any other characteristic protected by law.

Role Description As an AI Engineer NLP, you will design, develop, and deploy robust NLP systems for both medical devices and cloud environments. This role sits at the intersection of our NLP/ML team (Python) and platform/backend team (Go), requiring strong engineering capabilities across both domains to build scalable, production-grade AI systems. Key Responsibilities - Design, develop, and deploy agentic NLP systems and LLM-powered workflows across Python-based ML pipelines and Go-based backend services. - Act as a bridge between NLP and platform teams, translating ML requirements into scalable backend architectures and vice versa. - Contribute to both Python (ML/NLP) and Go (backend/platform) codebases, ensuring clean interfaces and efficient system integration. - Architect modular systems for LLM orchestration, APIs, and service communication (e.g., microservices, RPC, REST). - Ensure reliability, performance, and compliance of AI systems in regulated medical environments. - Implement evaluation, monitoring, and observability across the full stack (model + service layer). - Collaborate cross-functionally to deliver end-to-end AI-powered features from research to production. Qualifications - Strong Python engineering skills, including: - Advanced OOP, design patterns, and SOLID principles. - Experience with type-safe development (type hints, mypy, pydantic). - Writing tested, maintainable, and production-grade code. - Experience building and deploying LLM/NLP systems in production (e.g., LangChain, Google ADK, HuggingFace). - Experience or strong proficiency in backend development with Go, including API/service design. - Strong understanding of modern NLP/LLM workflows, including orchestration and evaluation. - Being native with Git version control and collaborative development workflows. - Ability to design systems with long-term scalability and maintainability in mind. Nice to Have - Experience in backend, frontend, or full-stack development beyond core responsibilities. What We Value - Ability to operate effectively across ML and backend engineering domains. - Engineering rigor applied to machine learning systems. - Clean, readable, and scalable code across languages. - Ownership mindset and proactive problem solving. - Ability to work independently while contributing to a collaborative environment. Working Conditions The environment is a typical start-up with an intrinsically motivated international team. Our company is an excellent place for rapid advancement and offers a promising opportunity to learn and share know-how in a very agile environment. The position requires the employee to go the extra mile when needed. We are looking for a team player who appreciates direct communication. The effort is rewarded with challenging tasks, the opportunity to take responsibility, a highly driven team, and work that serves a significant purpose. The job position comes with a competitive salary and a bonus for outstanding performance.

• You will own a product capability end to end, from architectural decisions through production outcomes, cutting through every layer: entry points, orchestration, intelligence, tools, data, and observability. • Your work directly shapes how Augeo's clients engage tens of millions of users. • You will build and ship mission-critical AI agents that drive revenue growth across finance, healthcare, telecom, and commerce. • Not proof-of-concepts. Powerful, scalable systems running in production. • Define how AI agents are built at Augeo. • Drive the Agent Development Life Cycle (ADLC) from initial pilot through production iteration, setting the standard for how agents are developed, tested, evaluated, and improved. • Build the shared platform: agent orchestration, agentic workflows, ML models, and data infrastructure that every product team at Augeo builds on. • Work across Augeo with engineers, product leads, and end users to understand needs, close feedback loops, and ensure the platform compounds with every interaction. • Shape the team. Participate in hiring and define the culture of an engineering org that is AI-native from day one.