Artificial Intelligence Agent Engineer

BRS is a government contracting and consulting firm supporting military installations and federal agencies. They are seeking an Artificial Intelligence Agent Engineer to design and operationalize intelligent software agents that utilize AI systems to automate workflows and enhance business outcomes.

Responsibilities:

• Designs, engineers, and operationalizes intelligent software agents that utilize large language models and AI systems to automate workflows, retrieve and reason over enterprise knowledge, and deliver business outcomes
• Applies principles of software engineering, information retrieval, and agent orchestration to construct production-grade agents that plan tasks, call tools and APIs, coordinate with other agents, and interact safely with users and services
• Architects end-to-end agent systems encompassing memory/state, retrieval layers, evaluation, and governance
• Integrates agents with cloud platforms and enterprise applications; establishes observability and lifecycle controls; and optimizes for accuracy, reliability, latency, scalability, and unit cost
• Collaborates with product, security, legal, and operations stakeholders to reimagine processes with agents at the center and align deployments with organizational standards and compliance requirements
• May lead technical reviews and mentor engineers contributing to shared frameworks, SDKs, and agent platforms
• Analyzes candidate business processes and user journeys to identify automation opportunities suitable for agentic patterns (planning, tool use, multi-step reasoning, delegation)
• Develops production-grade agents using modern frameworks and libraries and implements modular, testable code for skills, tools, connectors, and multi-agent collaboration
• Implements retrieval-augmented generation pipelines and curates embeddings, vector indexes, chunking strategies, and grounding policies to ensure factuality and source attribution
• Integrates agents with enterprise systems and external services (CRM, ticketing, knowledge bases, data warehouses, messaging, analytics) and manages identity, authorization, and auditability
• Engineers multi-agent communication and handoff mechanisms to enable cooperative task execution, error recovery, and fallback strategies
• Optimizes inference performance and cost and applies prompt and policy tuning, caching/batching, quantization, and model/vendor selection to meet service-level objectives
• Plans and executes versioning, testing, and rollout strategies (unit, integration, regression, UX)
• Maintains agent knowledge interfaces and schedules corpus refresh, drift detection, and policy updates to keep outputs aligned with evolving data and business rules
• Troubleshoots incidents spanning data, orchestration, inference, and integration layers
• Performs root-cause analysis and deploys durable fixes and post-incident improvements
• May engineer voice and telephony integrations, configure call routing and metadata exchange, and ensure audio quality and fallbacks for conversational agents
• May design synthetic-data generation and labeling workflows to expand evaluation coverage and accelerate tuning
• May participate in governance forums and vendor assessments, comparing models, orchestration frameworks, and hosting strategies against technical and commercial criteria
• Evaluates and recommends infrastructure and systems architecture; designs and validates server, storage, database, cloud, and network infrastructure solutions; develops and maintains architectural standards and technical documentation; identifies opportunities to improve performance, reliability, security, and automation; and collaborates with engineers and operations personnel to implement infrastructure enhancements
• Develops scripts and automation to streamline infrastructure management and operational processes and ensures infrastructure designs support cybersecurity, operational resiliency, and long-term organizational objectives