AI Engineer

ILS Inc. is seeking an AI Engineer to design and implement next-generation AI solutions using large language models (LLMs), agentic workflows, and Model Context Protocol (MCP)-based integrations. The ideal candidate has hands-on experience building AI-powered applications (not just training models) and understands how to orchestrate tools, APIs, and data sources into reliable systems. 

MUST BE LOCAL TO DC METRO AREA (hybrid support - 2 days in ILS HQ office, located in Fairfax, VA 22033

• →Design and build agentic AI systems that can reason, plan, and execute tasks using LLMs.
• →Implement integrations using Model Context Protocol (MCP) to connect AI agents with tools, APIs, and enterprise systems.
• →Develop and maintain LLM-powered applications (e.g., copilots, chat systems, automation tools).
• → Build prompt pipelines, tool-calling workflows, and multi-step reasoning systems.
• →Develop backend services using Java (Spring Boot) and/or Python to expose AI capabilities via APIs.
• →Leverage Spring AI or similar frameworks to integrate LLMs into enterprise applications.
• →Implement RAG (Retrieval-Augmented Generation) pipelines using vector databases.
• →Integrate AI solutions with cloud-native services such as AWS, Azure, and Google Cloud.
• → Deploy AI services and ensure scalability, reliability, and performance.
• →Collaborate with cross-functional teams in an Agile/Scrum environment.
• →Monitor and optimize AI systems for latency, cost, and output quality.

Required skill sets - Extensive experience with:

• Bachelor’s degree in computer science, Engineering, or related field.
• 5-9 years of professional experience in software engineering, AI engineering, or applied ML roles.
• Hands-on experience with LLM APIs.
•  Experience building agent-based workflows.
• ·Understanding of prompt engineering, tool usage, and structured outputs.
•  Familiarity with RAG architectures and vector databases.
• Experience with Model Context Protocol (MCP) or similar integration standards.
• Experience working with at least one cloud platform and exposure to others:
• AWS (Lambda, Bedrock, SageMaker, S3)
• Azure (Azure OpenAI, Functions, Cognitive Services)
• Google Cloud (Gemini Enterprise Agent Platform, Vertex AI, Cloud Functions, BigQuery)

• Strong programming skills in Python and/or Java.
• Experience building backend services using Spring Boot (REST APIs, microservices).
• Exposure to Spring AI or similar frameworks for integrating LLMs into Java applications.
• Experience with Docker and containerized deployments.
• Basic frontend experience (React, Angular) for AI-driven applications.
• Experience working in regulated environments (government, finance, healthcare).