Job DescriptionGenerative AI EngineerLocation: Remote (U.S.)
Salary Range: $120k to $170k
About the RoleWe are seeking a highly skilled Generative AI Engineer to lead the end-to-end delivery of production-grade AI systems. This role is responsible for designing, building, deploying, and continuously optimizing scalable generative AI solutions that integrate seamlessly with enterprise systems. You will act as a technical authority, shaping best practices and driving innovation across AI initiatives.
What You'll Do - Own the full lifecycle of generative AI systems, from architecture and development to deployment, monitoring, and optimization
- Design and build LLM-powered applications, including agent-based workflows, multi-step RAG pipelines, and enterprise AI solutions
- Establish and enforce engineering standards across prompt design, orchestration, structured outputs, and workflow lifecycle management
- Serve as a technical leader for GenAI, guiding architecture decisions and best practices
- Integrate AI systems with enterprise data, internal APIs, and cloud-native services
- Evaluate and select models, implement routing strategies, and optimize for latency, cost, and performance
- Continuously assess emerging AI tools and improve existing systems
- Own system performance across reliability, scalability, throughput, and cost efficiency
- Build and maintain observability frameworks (monitoring, tracing, logging, alerting)
- Design and manage CI/CD pipelines, including versioning and release processes
- Lead incident response and root cause analysis, implementing long-term fixes
- Develop evaluation pipelines for LLM outputs, including regression testing and failure analysis
- Implement safeguards such as human-in-the-loop workflows, schema validation, and output controls
- Ensure systems are secure against prompt injection, data leakage, and unauthorized access
- Collaborate with leadership and cross-functional teams to define and execute AI initiatives
- Provide hands-on technical guidance, mentoring, and code reviews
- Promote iterative delivery with frequent releases and continuous feedback loops
Required Qualifications - Proven experience building and deploying production-grade LLM or generative AI systems
- Strong expertise in prompt design, orchestration, and model tradeoffs
- Experience developing evaluation frameworks for AI outputs and validating quality
- Solid background in distributed systems and production software engineering
- Experience with CI/CD pipelines, release management, and operational ownership
- Demonstrated ability to define technical standards and influence architecture decisions
- Experience with cloud-native systems, APIs, and event-driven architectures (Azure or similar)
- Experience integrating AI solutions with enterprise data and security requirements
- Bachelor's degree in a technical field or equivalent practical experience
Preferred Qualifications - Experience with advanced RAG pipelines and agent-based AI systems in production
- Familiarity with cloud AI services and modern infrastructure tooling
- Experience with Python-based AI frameworks and data pipelines
- Experience with containerization and deploying AI workloads
- Knowledge of responsible AI practices and governance
- Domain experience in areas such as product data, ERP, ecommerce, or analytics platforms
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