Senior Agentic AI Software Engineer

LTS is seeking a Senior Agentic AI Software Engineer to build the intelligence behind their platform, focusing on autonomous agents and backend services. The role involves designing and developing AI systems that enhance software engineering through transparency and intelligent reasoning.

Responsibilities:

• 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

Requirements:

• 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
• Experience developing multi-agent AI systems and collaborative agent workflows
• Experience with OpenAI, Azure OpenAI, Anthropic Claude, Google Vertex AI, AWS Bedrock, or open-source LLMs
• Experience with vector databases such as Pinecone, Weaviate, Qdrant, Milvus, or Azure AI Search
• Experience implementing LLMOps or MLOps practices
• Familiarity with graph databases, knowledge graphs, or dependency analysis
• Experience working with software engineering tools, code intelligence platforms, or developer productivity products
• Experience building AI systems in healthcare, Federal Government, or other highly regulated environments
• Familiarity with Responsible AI, AI governance, privacy, security, and compliance best practices
• Experience using AI coding assistants and autonomous agents as part of daily software development