Senior AI Engineer

Description

Job Summary: We are seeking a Senior AI Engineer passionate about building cutting-edge Artificial Intelligence solutions—from research and prototyping to large-scale production. Key Highlights: 1. Impact education with innovative Data & AI solutions 2. Develop cutting-edge AI solutions for student and teacher experience 3. Work with Agentic Workflows, RAG, GraphRAG, SMLs, LLMs, and Generative AI Description: Our Data \& AI team is tasked with transforming education through innovative solutions focused on student and teacher experience, while delivering high business value. We seek a Senior AI Engineer passionate about building cutting-edge Artificial Intelligence solutions—from research and prototyping to large-scale production—collaborating closely with our Product, Operations, Pedagogical, and Educational Technology teams. Key Responsibilities: Support client squads in mapping technical and business requirements for AI solution development. Support client squads in building and presenting prototypes and experiments to validate solution hypotheses. Support the system design and solution design squad—comprising solution architects, data architects, and software architects—in designing robust, scalable low- and high-level solution architectures aligned with industry best practices. Design, implement, and operationalize solutions based on Agentic Workflows, RAG, GraphRAG, SMLs, LLMs, and Generative AI. Build and manage vector databases (Azure Vector Search, Elastic, and similar). Define and implement security and compliance guardrails (toxicity filters, bias mitigation, watermarking, hallucination prevention), aligned with Responsible AI frameworks. Define and implement semantic decomposition, vector memory, callback, cold-start, and fallback strategies for agents. Build monitoring and observability artifacts (Inference Latency, Token Usage, Error Rates, Output Quality, Model Drift, etc.), performance, cost, and response quality using Langsmith, LangTrace, Semantic Kernel, OpenTelemetry, Azure Monitor, Application Insights, Grafana, or similar tools. Orchestrate model versioning, continuous deployment (CI/CD), and artifact governance (MLflow, DVC). Optimize costs and latency via batching, quantization, sharding, and hyperparameter tuning. Desired Qualifications: Proven experience developing AI/ML solutions in production environments. Proven experience with Agentic Workflow projects using Azure OpenAI, CrewAI, PydanticAI, Langchain/LangGraph, or similar. Advanced knowledge of RAG, Graph RAG, SML, SQL Agents, vector databases, and high-dimensional embeddings. Advanced knowledge of prompt engineering, observability, fine-tuning, and evaluation of LLMs. Proven experience with MLOps (CI/CD, versioning, governance). Strong background in AI security, privacy, and ethics. Advanced Python programming and software engineering best practices. Nice-to-Have: Azure AI Engineer or Azure Data Scientist certification. Experience with LLM Routing. Knowledge of Kubernetes deployment and infrastructure-as-code (Terraform). Perks: * Remote work; * UNIMED health insurance; * Gympass; * 20 paid leave days; * Bonus/PLR; * Loyalty program (similar to 13th salary); * Referral bonus for new hires; * Birthday day-off. 2512180202551464020