Role Description GuidePoint Security is seeking an Applied AI Engineer to join our AI and Agentic Enablement practice. This is a mid-level engineering role for practitioners with hands-on experience designing and deploying agentic systems. The role spans harness development within existing agentic platforms, internal tooling for NE regional teams, and structured enablement programs that build lasting agentic capability across the organization. Working independently across the full delivery lifecycle, this engineer leads harness design and deployment, owns internal tooling initiatives, and drives the enablement programs that transfer agentic operating capability to regional teams. Roles and Responsibilities: - Design, build, and deploy agentic harnesses and LLM-integrated workflows from prototype through production within existing platforms. - Define and own performance benchmarks to evaluate reliability, accuracy, and continuous improvement of agentic pipelines. - Evaluate and recommend emerging AI tools, models, and platforms for adoption. - Identify, develop, and maintain AI-powered automations and tools that improve efficiency across service delivery, operations, and sales functions throughout the Northeast region. - Lead workflow assessments to identify opportunities for agentic automation and design repeatable, scalable delivery frameworks. - Own documentation, testing, and iteration on productized AI components and proof-of-concept builds for internal and client audiences. - Design and deliver enablement programs that build regional teams' capability to independently operate, maintain, and extend agentic harnesses. - Develop training materials and lead workshops that build agentic AI literacy across functional teams, including handoff documentation and runbooks. - Other duties as assigned. Qualifications - B.S. degree in computer science or relevant field and 3 years of experience or M.S. degree. - 3+ years of software development or AI/ML engineering experience. - Demonstrated ability to design, author, and deploy agentic harnesses within existing agentic platforms. - Working knowledge of Python and at least one additional language relevant to agentic development. - Working understanding of large language models, prompt engineering, and API-based AI integration. - Ability to independently scope, build, and ship agentic solutions at a mid-level engineering standard, ensuring secure development practices throughout. - Demonstrated ability to explain technical concepts to non-technical audiences. Requirements - Experience with cloud platforms (AWS, Azure, or Google Cloud), particularly AI/ML services. - Experience with vector databases, orchestration layers, or workflow automation platforms. - Experience with retrieval-augmented generation (RAG) patterns or tool-use/function-calling with LLMs. - Experience designing and applying evaluation frameworks and benchmarks for AI systems. - Experience designing and facilitating technical enablement programs for mixed audiences. Travel Requirements - Up to 10% travel. Physical Requirements - Sedentary work. - Substantial movement of the wrists, hands, and/or fingers for a minimum of 8 hours a day. - Required to have close visual acuity to view computer terminal and/or extensive reading for a minimum of 8 hours a day. Benefits - Remote workforce primarily (U.S. based only, some travel may be required for certain positions, working on-site may be required for Federal positions). - Group Medical Insurance options: Zero Deductible PPO Plan (GuidePoint pays 90% of the premium for employees and 70% for family plans) or High Deductible Health Plan with HSA (GuidePoint pays 100% of the employees premiums and 75% for family plans). - Group Dental Insurance: GuidePoint pays 100% of the premium for employees and 75% of family plans. - 12 corporate holidays and a Flexible Time Off (FTO) program. - Healthy mobile phone and home internet allowance. - Eligibility for retirement plan after 2 months at open enrollment. - Pet Benefit Option.

• Build and maintain shared infrastructure: secure web app hosting infrastructure, MCP/API standards, secret/key management, model selection, guardrails, and a centralized pattern library that all builders across the organization can pull from. • Own the review, tracking, and advisory process for all corporate AI and automation builds — MCP servers and tool configurations, Claude Skills, API integrations, and agentic workflows — before deployment. • Partner directly with AI specialists across departments to identify, scope, and build AI and automation solutions that meet high standards for cost, security, and scalability security before they ship. • Define and maintain the secure intake path for AI and automation requests across the organization, replacing ad-hoc builds and shadow IT with a governed, cost-effective, and scalable process. • Contribute to the organization’s AI cost efficiency by monitoring, alerting, and setting thresholds on AI spend across usage-based tools and platforms.

• Work closely with business stakeholders to rapidly develop, demonstrate, and refine AI solutions. • Take a hands-on engineering approach focused on building rather than advising. • Work directly with the client to translate business problems into AI-enabled prototypes and production-ready solutions.

• Have an immediate impact on how Homeward builds with AI. • Design, build, and maintain AI-powered features in our products, including LLM API integrations, retrieval-augmented generation (RAG) pipelines, and AI-driven automation across our customer, agent, and operations tools. • Understand and communicate requirements and • Build and improve shared tooling and reusable components that make it easier for teams across tech to access, integrate, and operate LLMs in production. • Contribute to the tooling we use to keep AI features reliable - observability, monitoring, evaluation, and prompt and context management - so we can measure and debug them with confidence. • Take on hard, ambiguous problems that can be solved leveraging LLMs and ML to solve real business problems, then help others learn how to solve similar problems. • Prototype solutions quickly, then work with peers and senior engineers to harden them into something we can ship and maintain. • Help shape the patterns and practices for building with AI at Homeward, and make the right way the easy way for the rest of the team. • Evaluate new models, tools, and approaches, recommend what's worth adopting, and help others adopt it. • Use AI coding assistants (Claude, Copilot) as a natural part of your daily workflow, and help the team get more out of them. • Write automated unit and integration tests to support our CI pipelines, and participate in code reviews. • Work closely with Product, Engineering, and Data to make sure what we build is useful, well-documented, and easy to adopt.