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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and building scalable Generative AI solutions, with a strong focus on backend development and integration of LLM APIs. Proficient in optimizing AI workflows and ensuring production readiness through effective debugging and performance evaluation.
Highest-signal resume keywords
Generative AI ExpertisePython DevelopmentLLM API IntegrationCloud Platform ExperienceDocker and Kubernetes Proficiency
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringBackend DevelopmentPrompt EngineeringRAG PipelinesMulti-Step AI WorkflowsPerformance EvaluationDebuggingSoftware ArchitectureEmbedding OptimizationCI/CD Pipelines
Soft Skills
CollaborationCommunication
Tools & Technologies
AWSAzureGCPDockerKubernetesGit
Industry Keywords
AI EngineeringProduction-Ready SolutionsQuality AssuranceScalabilityAccuracy
Tech Stack
Tools & technologiesAWSAzureCloudDockerGoogle Cloud PlatformKubernetesPython
About the role
Key responsibilities & impact- Design, build, and productionize scalable Generative AI solutions
- Focus on applied AI engineering and backend development
- Integrate LLM APIs into application workflows
- Build RAG pipelines and multi-step AI workflows
- Optimize AI-generated responses through prompt engineering, debugging, and performance evaluation
- Work closely with AI, DevOps, and software engineering teams
- Help deliver reliable, production-ready AI solutions while ensuring quality, accuracy, and scalability
Requirements
What you’ll need- 7+ years of software engineering experience, with a strong foundation in software architecture and engineering best practices
- Strong Python skills and proven experience developing and scaling backend services in production environments
- Deep technical knowledge of Generative AI, including LLM APIs, RAG pipelines, multi-step AI workflows, and prompt engineering
- Hands-on experience integrating foundational models into application workflows and using frameworks such as LlamaIndex and embedding optimization techniques
- Ability to evaluate, debug, and optimize AI-generated outputs for accuracy, bias, compliance, and performance
- Experience with cloud platforms such as AWS, Azure, or GCP
- Hands-on experience with Docker, Kubernetes, Git, and CI/CD pipelines
- Advanced English level
Benefits
Comp & perks- Salary in USD
- 100% Remote from Home
- 25 days of Paid Time Off per year
- 8-hour workday, with flexible hours
- Welcome kit from the brand
- High-end hardware provided: laptop, mouse, & headphones
- English classes, virtual library and online courses
- Contribution bonuses