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Applied AI Engineer (Agentic Systems)
Careers InitiateFirst
5 hours ago
Full-time
On-site
Atlanta, Georgia, United States
Requirements
Experience: 5-8 Years 5–8 years of professional experience, primarily in hands-on software engineering.Demonstrated ownership of production services, incident response and reliability improvement. Strong Python, with proficiency in at least one additional language. TypeScript is preferred for customer-facing applications and integration tooling. Demonstrable agentic work.Evidence of building and operating systems with tool use, multi-step orchestration and failure recovery for real users, including the ability to explain production failures and corrective changes. Working knowledge of retrieval and context engineering- embeddings, hybrid search, re‑ranking, context‑window economics and the ability to determine when retrieval is not the appropriate design. Evaluation discipline.Experience using offline and production evaluations as release gates, with automated scoring calibrated against human review. Framework judgement.Ability to choose between lightweight custom orchestration and a framework based on system complexity, maintainability and operational requirements. Business and technical communication.Ability to document architecture and decisions, communicate delivery status, and explain non-deterministic behaviour, risk and trade‑offs to accountable business and technology stakeholders Qualification
Bachelor’s degree in computer science, Engineering, or a related field
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Experience: 5-8 Years 5–8 years of professional experience, primarily in hands-on software engineering.Demonstrated ownership of production services, incident response and reliability improvement. Strong Python, with proficiency in at least one additional language. TypeScript is preferred for customer-facing applications and integration tooling. Demonstrable agentic work.Evidence of building and operating systems with tool use, multi-step orchestration and failure recovery for real users, including the ability to explain production failures and corrective changes. Working knowledge of retrieval and context engineering- embeddings, hybrid search, re‑ranking, context‑window economics and the ability to determine when retrieval is not the appropriate design. Evaluation discipline.Experience using offline and production evaluations as release gates, with automated scoring calibrated against human review. Framework judgement.Ability to choose between lightweight custom orchestration and a framework based on system complexity, maintainability and operational requirements. Business and technical communication.Ability to document architecture and decisions, communicate delivery status, and explain non-deterministic behaviour, risk and trade‑offs to accountable business and technology stakeholders Qualification
Bachelor’s degree in computer science, Engineering, or a related field
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