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Senior Applied AI Engineer
Location
United States
Posted
1 day ago
Salary
0
Seniority
Senior
Job Description
Senior Applied AI Engineer
Givzey
• Design, build, and maintain production-grade AI systems and customer-facing AI features • Develop agentic workflows using LLMs, retrieval systems, tools, APIs, and backend services • Build backend services, orchestration systems, automation, and infrastructure supporting AI-powered workflows • Design and implement retrieval-augmented generation (RAG) systems, including ingestion pipelines, embeddings, semantic retrieval, and context assembly • Integrate foundation models through platforms such as Amazon Bedrock or Agent Core • Develop robust prompting strategies, structured outputs, guardrails, and workflow logic for production use cases • Implement evaluation systems for prompts, agents, and workflows, including regression testing, trace review, golden datasets, and human QA processes • Monitor and improve production AI systems for quality, reliability, latency, observability, and cost efficiency • Debug AI behavior through logs, traces, evaluations, user feedback, and production telemetry • Collaborate closely with engineering, product, operations, and customer-facing teams to turn ambiguous requirements into reliable systems • Help establish strong engineering standards around testing, deployment, CI/CD, version control workflows, code review, and operational reliability • Mentor and collaborate with engineers across both software and AI disciplines • Evaluate emerging AI technologies pragmatically based on business impact, maintainability, and operational reliability
Job Requirements
- US Citizen or authorized to work in US
- 5+ years of professional software engineering experience building production systems
- Strong proficiency in Python
- Strong backend engineering fundamentals and experience building scalable APIs, services, distributed systems, or workflow orchestration platforms
- Proven hands-on experience building and shipping AI-powered applications using LLMs, generative AI APIs, agents, retrieval systems, or related technologies in production environments
- Experience designing and implementing agentic workflows, tool-calling systems, structured outputs, prompt pipelines, or retrieval-augmented generation architectures
- Strong understanding of the practical challenges involved in production AI systems, including hallucination mitigation, evaluation, reliability, observability, latency, and cost management
- Experience building production software systems with strong engineering standards around testing, QA, deployment, monitoring, and maintainability
- Strong understanding of modern software engineering practices, including Git workflows, code review, CI/CD, automated testing, operational debugging, and release management
- Experience working with cloud infrastructure, preferably AWS
- Experience working with SQL and/or NoSQL databases
- Strong debugging, systems-thinking, and problem-solving skills
- Ability to operate effectively in fast-moving environments with evolving requirements and imperfect information
- Strong communication skills and ability to collaborate across technical and non-technical teams
Benefits
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
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