• Building scalable backend systems • Designing APIs • Collaborating with cross-functional teams to deliver robust solutions that power real-world products

• Lead the design and implementation of major features and services within the Platform Catalog ecosystem. • Drive architectural discussions and propose scalable, reliable solutions aligned with engineering best practices. • Mentor junior engineers and promote a culture of technical excellence, collaboration, and continuous learning. • Partner with product managers and stakeholders to translate business goals into technical deliverables. • Advocate for system reliability, performance, and observability across multiple integrations and services. • Apply strong software engineering principles using Java, REST/GraphQL APIs, Docker, and Kubernetes to design and build backend applications that power advertising and data-driven platforms. • Utilize Kafka, Aerospike, and Elasticsearch to develop real-time data pipelines that serve as the backbone for critical business operations. • Design and implement microservices architectures for highly available, large-scale distributed systems. • Participate in and manage on-call rotations to troubleshoot and resolve system issues during off-hours or high-traffic events. • Coordinate with team members to assign tasks, set goals, monitor progress, and resolve technical challenges effectively. • Provide technical mentoring and guidance to team members, fostering professional growth and knowledge sharing.

• You will join our team in a unique position. • For the first few months, you will work on maintaining and supporting legacy systems while getting to know our engineering practices and team. • After that initial phase, you will transition to our core development team where you will work on our modern tech stack. • Full Stack Development • Build and maintain applications using Java and Angular • Design and consume REST and GraphQL APIs • Work across the full request cycle from database to user interface • Design database schemas and write performant queries • Deploy and operate services in cloud environments • Improve monitoring, logging, and system reliability • Support incident response and root cause analysis • Keep systems running reliably in mission critical environments

• Develop agentic AI workflows using LangChain/LangGraph with custom tools, memory, decision logic, and MCP integrations. • Implement LLM applications with advanced prompt engineering (structured outputs, function calling, context management) and build RAG pipelines with vector databases. • Build and deploy event-driven AI services on AWS using Bedrock, SageMaker, Lambda, EventBridge, Step Functions, API Gateway, DynamoDB, and S3. • Write clean, testable Python code; create unit/integration tests; and package solutions with CI/CD pipelines (GitHub Actions). • Monitor and optimize AI application performance through logging, metrics, token usage, and cost management. • Integrate AI services with APIs, backend systems, and databases to ensure secure and reliable data flow. • Contribute to document AI and predictive analytics models for information extraction, classification, and forecasting. • Fine-tune Hugging Face Transformer models (BERT, RoBERTa, LayoutLM, DistilBERT) and train neural networks (PyTorch/TensorFlow) for supervised tasks. • Implement data preprocessing and annotation workflows for training and evaluation. • Work with OCR and text-processing tools (AWS Textract, Tesseract) for semi-structured/unstructured documents.