Senior Applied AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Create, develop, and sustain production-quality AI systems and customer-oriented AI functionalities.

• Construct agentic workflows utilizing LLMs, retrieval systems, tools, APIs, and backend services.

• Develop backend services, orchestration frameworks, automation, and infrastructure to support AI-driven workflows.

• Design and execute retrieval-augmented generation (RAG) systems, encompassing ingestion pipelines, embeddings, semantic retrieval, and context assembly.

• Integrate foundational models via platforms such as Amazon Bedrock or Agent Core.

• Formulate effective prompting strategies, structured outputs, guardrails, and workflow logic for production scenarios.

• Establish evaluation systems for prompts, agents, and workflows, including regression testing, trace reviews, golden datasets, and human quality assurance processes.

• Supervise and enhance production AI systems regarding quality, reliability, latency, observability, and cost-effectiveness.

• Diagnose AI behavior through logs, traces, evaluations, user feedback, and production telemetry.

• Work closely with engineering, product, operations, and customer-facing teams to transform ambiguous requirements into dependable systems.

• Assist in establishing robust engineering standards concerning testing, deployment, CI/CD, version control workflows, code reviews, and operational reliability.

• Mentor and work collaboratively with engineers across both software and AI domains.

• Assess emerging AI technologies pragmatically based on business impact, maintainability, and operational reliability.

⛳️ Requirements

• U.S. Citizen or authorized to work in the U.S.

• Over 5 years of professional software engineering experience in building production systems.

• Strong proficiency in Python programming.

• Solid backend engineering fundamentals along with experience in developing scalable APIs, services, distributed systems, or workflow orchestration platforms.

• Demonstrated hands-on experience in creating and delivering AI-powered applications using LLMs, generative AI APIs, agents, retrieval systems, or similar technologies in production settings.

• Experience in designing and implementing agentic workflows, tool-calling systems, structured outputs, prompt pipelines, or retrieval-augmented generation architectures.

• Comprehensive understanding of the practical challenges associated with production AI systems, including hallucination mitigation, evaluation, reliability, observability, latency, and cost management.

• Experience in developing production software systems with strong engineering standards concerning testing, quality assurance, deployment, monitoring, and maintainability.

• Solid grasp of modern software engineering practices, including Git workflows, code reviews, CI/CD, automated testing, operational debugging, and release management.

• Experience with cloud infrastructure, preferably AWS.

• Familiarity with SQL and/or NoSQL databases.

• Strong debugging, systems-thinking, and problem-solving capabilities.

• Ability to function effectively in fast-paced environments with changing requirements and incomplete information.

• Excellent communication skills and ability to collaborate across both technical and non-technical teams.

🏝️ Benefits

• Health insurance.

• Retirement plans.

• Paid time off.

• Flexible work arrangements.

• Professional development.