PositionAI/ML Agentic Engineer - Location: Fort Walton Beach, FL
- Security Clearance: Active Clearance or Eligible to Obtain - U.S. citizenship required
- Salary: $115,000 - $135,000 Depending on Experience and Education
- Travel: 5%
- Benefits: SURVICE Engineering offers a total rewards package to include competitive salaries, comprehensive insurance options, paid time off, 401k, flexible spending, tuition reimbursement.
Position SummarySURVICE Engineering is currently seeking a
AI/ML Agentic Engineer to support our Gulf Coast Operation. You will accelerate your career and become an integral team member within the defense community.
Primary Duties and Responsibilities- Build AI Agents: Design and develop autonomous AI systems using Large Language Models (LLMs)
- Connect Tools: Integrate AI models with external software, APIs, and databases so agents can take real actions
- Optimize Workflows: Test, debug, and improve how agents plan, reason, and execute multi-step tasks
• Write Code: Write clean, fast, and reliable .NET/Python code for production environments
• Collaborate: Work closely with product managers and other engineers to ship new AI features
Minimum Qualifications of AI/ML Agentic EngineerBachelor's Degree in Computer Science/Computer Engineering or related discipline and 2+ years of relevant experience. Exceptional candidates with less experience will be considered. Candidates are not required to possess all qualifications; if you possess some of the desired qualifications, please apply.
- Experience: 2+ years of professional software engineering or machine learning experience
- Programming: Strong proficiency in .NET/Python and modern software development practices
- AI/LLM Knowledge: Hands-on experience working with LLM APIs (such as OpenAI, Anthropic, or open-source models)
- Agent Frameworks: Familiarity with agentic frameworks like Microsoft.Agent.Framework, LangChain, and/or LlamaIndex
- Databases: Basic understanding of vector databases (like Pinecone, Chroma, pgvector, or SQL Server 2025) and Retrieval-Augmented Generation (RAG)
- Problem-Solving: A curiosity for how AI works and a drive to solve tricky automation challenges
- MCP: Experience using Model Context Protocol for Agent tooling
