{"schemaVersion":"jobsearcher.job.v1","id":"bf605bb7aef1c9afd8d3f3d1","url":"https://jobsearcher.com/jobs/bf605bb7aef1c9afd8d3f3d1","canonicalUrl":"https://jobsearcher.com/jobs/bf605bb7aef1c9afd8d3f3d1","title":"AI Engineer (GenAI & Agentic Systems)","description":"Overview\nIn this role you design, prototype, and implement GenAI-powered automations and agentic workflows to support knowledge work and decision making. You work on POCs/MVPs with LLMs, SLMs, RAG, and agentic patterns, evaluating third‑party AI capabilities and integrating them into enterprise systems. You deliver reliable inference pipelines, design prompts, and apply guardrails to manage risk and cost. This role sits at the intersection of engineering, product, and governance to scale responsible AI in an enterprise setting.\n\nResponsibilitiesGenAI POC and MVP development using LLMs/SLMs, tools, and agentsDesign and implement GenAI inference pipelines for structured and unstructured inputs; support real-time, batch, and asynchronous modesPrompt engineering and data feature engineering for GenAIDesign and prototype agentic automations that decompose tasks, plan, invoke tools/APIs, and handle errors/retriesIntegrate agents with AI platforms and source APIs; apply guardrails for autonomy, cost, and riskEvaluate GenAI features in SaaS/COTS products; assess usage, prompts, customization, API readiness, observability, and governance input to decisions\nKey requirementsStrong Python and API-based service developmentHands-on experience with LLMs/SLMs, RAG, prompt engineering, and agentic patternsExperience building GenAI inference pipelinesUnderstanding of API-first and event-driven architecturesExperience integrating AI services with enterprise systems and SaaS platformsDeep understanding of GenAI vs traditional systems and agent autonomy vs control tradeoffsAbility to translate experiments into reliable, automated AI systemsStrong collaboration across engineering, product, data, and governance teamscollaboration across multiple teamscommunicationproblem solvingPythonLLMs and SLMsRAG (retrieval-augmented generation)","company":"Ampcus","rawCompany":"ampcus","city":"McLean","state":"VA","isRemote":false,"isActive":false,"createdAt":"2026-09-15T03:35:21.367Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"17-2199.00","title":"Engineers, All Other","slug":"engineers-all-other"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"AI Engineer (GenAI & Agentic Systems)","description":"Overview\nIn this role you design, prototype, and implement GenAI-powered automations and agentic workflows to support knowledge work and decision making. You work on POCs/MVPs with LLMs, SLMs, RAG, and agentic patterns, evaluating third‑party AI capabilities and integrating them into enterprise systems. You deliver reliable inference pipelines, design prompts, and apply guardrails to manage risk and cost. This role sits at the intersection of engineering, product, and governance to scale responsible AI in an enterprise setting.\n\nResponsibilitiesGenAI POC and MVP development using LLMs/SLMs, tools, and agentsDesign and implement GenAI inference pipelines for structured and unstructured inputs; support real-time, batch, and asynchronous modesPrompt engineering and data feature engineering for GenAIDesign and prototype agentic automations that decompose tasks, plan, invoke tools/APIs, and handle errors/retriesIntegrate agents with AI platforms and source APIs; apply guardrails for autonomy, cost, and riskEvaluate GenAI features in SaaS/COTS products; assess usage, prompts, customization, API readiness, observability, and governance input to decisions\nKey requirementsStrong Python and API-based service developmentHands-on experience with LLMs/SLMs, RAG, prompt engineering, and agentic patternsExperience building GenAI inference pipelinesUnderstanding of API-first and event-driven architecturesExperience integrating AI services with enterprise systems and SaaS platformsDeep understanding of GenAI vs traditional systems and agent autonomy vs control tradeoffsAbility to translate experiments into reliable, automated AI systemsStrong collaboration across engineering, product, data, and governance teamscollaboration across multiple teamscommunicationproblem solvingPythonLLMs and SLMsRAG (retrieval-augmented generation)","datePosted":"2026-09-15T03:35:21.367Z","dateModified":"2026-09-15T03:35:21.367Z","hiringOrganization":{"@type":"Organization","name":"Ampcus","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"McLean","addressRegion":"VA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"bf605bb7aef1c9afd8d3f3d1"},"url":"https://jobsearcher.com/jobs/bf605bb7aef1c9afd8d3f3d1"}}