Senior Agentic AI Software Engineer

🕒 vor 6 Tagen

🇺🇸 Vereinigte Staaten – Remote

⏰ Vollzeit

🟠 Senior

🤖 KI-Ingenieur

🦅 H1B-Visum-Sponsor

Dieses Unternehmen hat in der Vergangenheit H1B-Visa gesponsert.

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LTS

WebsiteLinkedInAlle Stellen

1001 - 5000 Mitarbeiter

🏥 Gesundheitswesen

💼 Beratung

📦 Logistik

Healthcare • Consulting • Logistics

LTS ist ein Unternehmen, das sich auf missionsunterstützende Dienstleistungen und Gesundheitsdienste für Behörden konzentriert und Notfallmaßnahmen, Arbeitsschutz, automatisierte Gesundheitslösungen und Unternehmensberatung anbietet. Es bietet schnelle landesweite Einsätze für Katastrophenhilfe, Logistik und Massenbetreuung und liefert automatisierte Diagnostik-Kioske, Labortests, medizinisches Personal, Vor-Ort-Kliniken sowie das Management von Tests und Impfungen für benachteiligte und abgelegene Bevölkerungsgruppen. LTS bietet außerdem IT-Modernisierung, Cloud- und Systemintegration, Cybersecurity und Risikomanagement, KI/ML und Datenanalysen sowie Programmmanagement für Bundes-, Landes- und Kommunalkunden mit starker Compliance (HIPAA und Bundesstandards) und Erfahrung im Bereich öffentlicher Ausschreibungen.

Beschreibung

• Design, develop, and deploy autonomous and multi-agent AI systems capable of reasoning, planning, tool use, workflow automation, and human-in-the-loop collaboration. • Build intelligent orchestration pipelines coordinating LLMs, specialized agents, enterprise tools, and structured reasoning workflows. • Develop reusable agent architectures and orchestration patterns that accelerate intelligent application development across the platform. • Design and optimize Retrieval-Augmented Generation (RAG) pipelines including document ingestion, embeddings, hybrid retrieval, reranking, semantic search, context engineering, and prompt orchestration. • Integrate AI systems with source code repositories, enterprise documentation, APIs, structured data, and knowledge repositories. • Ensure every AI-generated response is explainable, evidence-based, and traceable to authoritative sources. • Design and implement scalable backend services, APIs, and cloud-native applications supporting enterprise AI workloads. • Develop distributed systems capable of serving low-latency AI experiences while maintaining security, reliability, and observability. • Optimize performance, latency, throughput, model quality, and infrastructure cost across production AI systems. • Implement testing, evaluation, monitoring, observability, guardrails, and LLMOps practices to ensure AI systems remain trustworthy and production-ready. • Continuously evaluate emerging models, frameworks, and engineering practices to improve platform capabilities. • Build AI systems that behave predictably in highly regulated enterprise environments. • Partner closely with AI architects, platform engineers, front-end engineers, designers, and product leaders to deliver cohesive AI-powered experiences. • Mentor engineers through technical leadership, architecture discussions, design reviews, and collaborative problem solving. • Help establish engineering standards, reusable frameworks, and best practices across the AI engineering organization.

🎯 Anforderungen

• Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Engineering, or a related technical discipline (or equivalent professional experience). • 7+ years of professional software engineering experience designing and building distributed production systems. • At least 3 years designing, developing, and deploying production AI applications beyond proof-of-concept environments. • Strong proficiency in Python and modern backend software engineering. • Experience building enterprise APIs, microservices, and cloud-native applications. • Hands-on experience developing applications powered by Large Language Models (LLMs) and Generative AI. • Experience building Agentic AI solutions using frameworks such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or comparable technologies. • Strong experience designing Retrieval-Augmented Generation (RAG) architectures including embeddings, vector search, hybrid retrieval, reranking, context engineering, and grounding techniques. • Experience integrating AI systems with enterprise APIs, databases, cloud platforms, and business applications. • Experience with Docker, Kubernetes, Git, CI/CD pipelines, and modern DevOps practices. • Strong understanding of software architecture, testing, observability, debugging, and production operations. • Excellent communication skills with the ability to explain complex technical concepts to both engineering and business stakeholders. • Ability to solve difficult engineering problems from first principles. • Ability to think deeply about system architecture, reliability, and scalability. • Passionate about explainability as model performance. • Ability to move comfortably between distributed systems, AI frameworks, and product engineering. • Willingness to take ownership of ambiguous, high-impact technical challenges. • Background with using AI coding assistants, autonomous agents, and model-driven engineering workflows. • A technically skilled engineer with a preference for building products that create lasting impact over incremental feature development.

🏖️ Vorteile

• Comprehensive benefits for you and your family • Access to cutting-edge tools and technologies • A culture that values innovation, growth, and collaboration • The Opportunity to support high-visibility federal missions • A career path that rewards ambition and performance