Generative AI Engineer Location: Remote (U.S.) Salary Range: $120k to $170k About the Role We 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 Youll 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
Bachelors 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