Senior AI Engineer Software Engineer Government Technology

ICON is looking for a pragmatic builder who has made the leap from traditional software engineering into the emerging world of agentic AI development to join our Government Technology team. As an AI Software Engineer at ICON, you will be responsible for designing and shipping AI-powered tools, workflows, and autonomous agents that accelerate ICON's construction technology platform. This role reports to the Senior Director, Defense Technology Programs and is a full-time on-site position based on our Austin, TX campus. RESPONSIBILITIES Design and build agentic AI systems that automate complex, multi-step workflows across ICON's software platform Develop LLM-powered features and products using state-of-the-art foundation models and APIs (e.g. Anthropic, OpenAI) Architect and implement multi-agent pipelines, tool-use systems, and Model Context Protocol (MCP) integrations Build robust RAG systems including document ingestion, chunking strategies, embedding pipelines, and vector retrieval Collaborate with software and domain teams to identify high-leverage AI automation opportunities and translate them into shipped products Own the full development lifecycle of AI features: prototyping, evaluation, deployment, and iteration Serve as a technical resource and informal mentor on agentic AI best practices across the engineering organization Stay at the leading edge of the agentic AI landscape and bring emerging techniques into production MINIMUM QUALIFICATIONS 8+ years of professional software engineering experience with a strong foundation in backend or full-stack development Demonstrated experience building and shipping production-grade products using LLMs and agentic frameworks Proficiency in TypeScript and/or Python Deep understanding of prompt engineering, context management, and LLM reasoning patterns Experience with tool-use, function calling, and agent orchestration (e.g. LangChain, LlamaIndex, Claude Code, or custom implementations) Proficiency in the design and execution of structured evals to measure and improve AI system performance Strong communication skills and comfort working cross-functionally with both technical teams and non-technical stakeholders Experience working in or alongside government, defense, or regulated environments Strong experience working with code generation agents (e.g. Claude Code, Cursor, Devin-style systems) PREFERRED SKILLS AND EXPERIENCE Experience with MCP (Model Context Protocol) server development and integration Familiarity with vector databases (e.g. pgvector, Pinecone, Weaviate) Experience with fine-tuning, RLHF, or model evaluation pipelines Strong background in ML fundamentals: embeddings, transformers, attention mechanisms Exposure to structured output generation and LLM-based data extraction Familiarity with AWS and serverless infrastructure for AI workloads Interest or background in the AEC (architecture, engineering, construction) industry ICON is an equal opportunity employer committed to fostering an innovative, inclusive, diverse and discrimination-free work environment. Employment with ICON is based on merit, competence, and qualifications. It is our policy to administer all personnel actions, including recruiting, hiring, training, and promoting employees, without regard to race, color, religion, gender, sexual orientation, gender identity, national origin or ancestry, age, disability, marital status, veteran status or any other legally protected classification in accordance with applicable federal and state laws. Consistent with the obligations of these laws, ICON will make reasonable accommodations for qualified individuals with disabilities. Furthermore, as a federal government contractor, the Company maintains an affirmative action program which furthers its commitment and complies with record‑keeping and reporting requirements under certain federal civil rights laws and regulations, including Executive Order 11246, Section 503 of the Rehabilitation Act of 1973 (as amended) and the Vietnam Era Veterans' Readjustment Assistance Act of 1974 (as amended). #J-18808-Ljbffr