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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 deploying production-ready applications using Large Language Models (LLMs) and AWS Bedrock, with a strong focus on prompt engineering, AI system optimization, and backend development using Python. Proficient in implementing scalable AI architectures and integrating with enterprise systems while ensuring performance and quality through effective monitoring solutions.
Highest-signal resume keywords
Large Language Models (LLMs)AWS BedrockPrompt EngineeringPython DevelopmentAgentic Architecture
ATS Keywords
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Hard Skills
Full-Stack DevelopmentAI Pipeline DesignContainerization StrategiesAPI DevelopmentModel Fine-TuningHyperparameter OptimizationVector DatabasesEmbedding ModelsKnowledge GraphsDevOps Practices
Soft Skills
Stakeholder CollaborationTechnical Documentation
Tools & Technologies
LangChainLlamaIndexCrewAIAutoGenPineconeWeaviateOpenSearch
Industry Keywords
Generative AIRAG ArchitecturesMulti-Agent AI SystemsCI/CD Pipelines
Tech Stack
Tools & technologiesAWSPython
About the role
Key responsibilities & impact- Design, develop, and deploy production-ready applications using LLMs and foundation models through AWS Bedrock
- Build and optimize RAG architectures for large-scale document repositories
- Implement and orchestrate multi-agent AI systems using AWS Bedrock Agents and AgentCore frameworks
- Design scalable AI pipelines integrating with enterprise systems
- Develop backend services and APIs for AI applications using Python and modern frameworks
- Implement containerization and deployment strategies
- Build monitoring and observability solutions for AI system performance, quality, and costs
- Design and optimize prompts and templates for LLM behavior
- Apply advanced prompt engineering techniques
- Evaluate and fine-tune models for specific use cases
- Experiment with model configurations, hyperparameters, and architectures
- Partner with stakeholders to translate requirements into technical solutions
- Evaluate emerging foundation models and generative AI research
- Contribute to technical documentation, best practices, and knowledge sharing
- Participate in Generative AI-related sales initiatives
Requirements
What you’ll need- Strong years of professional software engineering experience
- Full-stack development experience
- Hands-on experience with Large Language Models (LLMs) and foundation model APIs
- Experience with agentic architecture and implementation, such as LangChain, LlamaIndex, CrewAI, and AutoGen
- Prompt engineering and optimization techniques
- Experience using vector databases such as Pinecone, Weaviate, and OpenSearch
- Experience with embedding models or Knowledge Graphs
- Knowledge of DevOps practices and CI/CD pipelines for AI applications
- Knowledge of Python with modern frameworks and libraries
Benefits
Comp & perks- Health and dental insurance
- Meal and food allowance
- Childcare assistance
- Extended paternity leave
- Partnership with gyms and health and wellness professionals via Wellhub (Gympass) TotalPass
- Profit Sharing and Results Participation (PLR)
- Life insurance
- Continuous learning platform (CI&T University)
- Discount club
- Free online platform dedicated to physical, mental, and overall well-being
- Pregnancy and responsible parenting course
- Partnerships with online learning platforms
- Language learning platform
- Health and well-being team support
- Inclusion specialists and affinity groups
- Support obtaining disability assessment and workplace accommodations