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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in integrating AI models with real-world systems, focusing on backend development with Python, API management, and LLM utilization. Proficient in implementing security measures and optimizing conversational AI through effective orchestration and context management.
Highest-signal resume keywords
LLM Use And Prompt EngineeringBackend Development With PythonAI Orchestration FrameworksBuilding And Maintaining RAG PipelinesAPI Management And Security
ATS Keywords
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Hard Skills
PythonREST APIsWebhooksRAG PipelinesLLM Tracing ToolsGitDockerRelational DatabasesNoSQL DatabasesAsynchronous Processing
Tools & Technologies
LangChainLangGraphLlamaIndexLangfuseLangSmithRedisSQSCelery
Industry Keywords
B2CB2BConversational State MachinesContext RetrievalError HandlingSecurityFunction CallingAutomated EvaluationModel Context Protocol
Tech Stack
Tools & technologiesDockerNoSQLPythonRedis
About the role
Key responsibilities & impact- Integrate AI models with real-world systems for B2C and B2B journeys
- Develop and maintain standardized APIs and webhooks as tools for the AI agent
- Ensure security and rigorous error handling across APIs and webhooks
- Support the design and maintenance of conversational state machines/graphs
- Manage interaction context in long-running conversations
- Monitor and fine-tune context retrieval from the knowledge base
- Refine the data provided to the LLM to improve response accuracy
- Collaborate with Senior Engineers on architectural improvements
- Analyze production metrics
- Implement new security and orchestration layers
Requirements
What you’ll need- Practical understanding of LLM use and Prompt Engineering techniques, including hallucination mitigation, context-window management, and structured output generation (JSON/Pydantic)
- Hands-on experience building and maintaining RAG pipelines (ingestion, chunking, embedding generation, and searches in vector databases)
- Ability to securely connect LLMs to external systems through Function Calling (Tools), with robust input and output data validation
- Strong backend development experience with Python, including consuming and creating REST APIs, webhooks, and authentication
- Ability to debug and analyze model responses, supporting the creation of test cases
- Hands-on experience with AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or similar tools
- Practical use of LLM tracing tools such as Langfuse, LangSmith, or similar tools
- Proficiency with Git, Docker, and relational/NoSQL databases
- Basic knowledge of queues and asynchronous processing, such as Redis, SQS, or Celery
- Familiarity with automated evaluation (EVAL) methodologies, including LLM-as-a-judge — optional
- Interest in and knowledge of the Model Context Protocol (MCP) — optional
Benefits
Comp & perks- Health and dental insurance
- Meal and food allowances
- Childcare assistance
- Extended parental leave
- Partnerships with gyms and health and wellness professionals through Wellhub (Gympass) and TotalPass
- Profit-sharing and performance bonus (PLR)
- Life insurance
- Continuous learning platform (CI&T University)
- Discount club
- Free online platform dedicated to promoting physical and mental health and well-being
- Pregnancy and responsible parenting course
- Partnerships with online course platforms
- Language-learning platform
- Support and accommodations for people with disabilities
- Assistance obtaining disability documentation
- Dedicated Health and Well-being team
- Inclusion specialists and affinity groups