About This OpportunityThe AI Solutions Engineer is an experienced, hands-on technology professional responsible for designing, building, and deploying intelligent solutions across the enterprise. Working directly with business and technology leaders, this role identifies high-value opportunities, translates operational needs into technical solutions, and moves AI capabilities from concept into secure, reliable, scalable, and cost-effective production use.
This opportunity spans the organization and may include agent-assisted RFQ and proposal development, engineering knowledge retrieval, manufacturing and supply-chain decision support, service and aftermarket workflows, finance automation, and employee productivity. The successful candidate will be equally comfortable developing software, integrating enterprise data and systems, and partnering with stakeholders to deliver measurable business outcomes. Reporting to the Vice President, Information Systems, this position is based in Komline's Washington, DC office and requires approximately 25% travel, primarily to Komline operating locations.
Responsibilities- Partner with business leaders and subject-matter experts to identify and prioritize AI opportunities based on business value, feasibility, risk, data readiness, and adoption requirements
- Design, build, test, and deploy scalable AI agents and applications that reason over enterprise information, use approved tools, call APIs, and support multi-step business workflows
- Develop retrieval-augmented generation, enterprise search, document processing, structured extraction, classification, summarization, and related knowledge capabilities
- Integrate AI solutions with platforms and data sources such as Microsoft 365, Dynamics 365, Salesforce, Microsoft Fabric, Azure data services, and other operational systems
- Use Komline's enterprise ChatGPT, Claude, and Microsoft Copilot capabilities to develop repeatable agents, assistants, applications, and workflows when those platforms provide the best fit
- Design solutions for increasing usage and data volumes while managing model selection, context size, token and credit consumption, caching, rate limits, latency, and other cost and performance drivers
- Create reusable services, components, prompts, tools, connectors, and solution patterns that accelerate delivery of future AI use cases
- Establish test suites and evaluation methods for accuracy, relevance, latency, reliability, safety, cost, and business effectiveness, and use results to improve solutions before and after launch
- Implement appropriate human-in-the-loop controls, identity and access safeguards, logging, monitoring, exception handling, and data-protection practices
- Build prototypes quickly and harden successful concepts for production through sound architecture, load and performance testing, documentation, version control, deployment, monitoring, and support practices
- Evaluate enterprise platforms, models, custom approaches, and third-party products; develop build-versus-buy recommendations, implementation estimates, architecture approaches, and ROI analyses
- Demonstrate solutions, gather user feedback, document workflows, and help business teams incorporate new capabilities into day-to-day work
- Monitor solution performance, consumption, adoption, and business outcomes; communicate priorities, progress, risks, and realized value to stakeholders
- Maintain a practical backlog of enhancements and new use cases and contribute technical guidance to Komline's AI architecture, standards, governance, and responsible-use practices
- Perform other duties as assigned
Qualifications- 3+ years of professional experience implementing AI, machine learning, data, or software solutions, including hands-on delivery of AI-enabled applications in a business environment
- Demonstrated experience building with large language models, including agent orchestration, tool or function calling, structured outputs, prompt design, grounding, retrieval-augmented generation, and model evaluation
- Strong programming skills in Python and experience developing and consuming REST APIs, working with JSON, and integrating cloud or enterprise systems
- Experience with modern software development practices, including Git, testing, code review, CI/CD, deployment, logging, monitoring, and production support
- Experience designing AI or cloud solutions for scalability, performance, and cost efficiency, including practical management of model usage, context windows, token consumption, caching, throughput, and rate limits
- Working knowledge of cloud AI and data services
- Ability to work with structured and unstructured data, including documents, databases, APIs, and vector search technologies
- Understanding of enterprise security, privacy, identity, access control, data protection, and responsible AI considerations
- Strong analytical, verbal, and written communication skills, with the ability to translate business problems into technical designs and explain technical tradeoffs to nontechnical stakeholders
- Ability to work effectively with business, IT, data, security, and executive stakeholders in a cross-functional environment
- Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field, or equivalent practical experience
Preferred- Experience deploying agentic systems or large language model applications using orchestration frameworks or cloud-native AI platforms
- Experience developing enterprise solutions using ChatGPT Enterprise, Claude Enterprise, Microsoft Copilot, Copilot Studio, or comparable governed AI platforms
- Experience with Azure AI services, Azure OpenAI, Microsoft Fabric, Power Platform, or related Microsoft technologies
- Experience with document intelligence, knowledge management, workflow automation, or enterprise search
- Experience integrating AI with ERP, CRM, engineering, manufacturing, or service-management systems
- Familiarity with industrial manufacturing, made-to-order, engineer-to-order, or other complex business-to-business environments
