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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer - Brand Safety & Agentic AI - **Company:** SocialEdge, Inc. - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Automation of Tests, Batch Processing, Big Data, Cloud Database, Software Quality, Code Review, Databases, Continuous Integration, Extract Transform Load (ETL), Relational Databases, DevOps, Python (Programming Language), Key Management, PostgreSQL, Machine Learning, Microsoft SQL Server, Node.Js, Software Architecture, Query Optimization, Cloud Services, Software Engineering, Data Streaming, Systems Integration, TypeScript, Parquet, Data Processing, ReactJS, Concurrency, Generative AI, AWS Lambda, Backend, Agentic-AI, Rate Limiting, Servicebus, Event Driven Architecture, Amazon Relational Database Service, AWS Aurora, CrewAI, Integration Frameworks, Graphql, Api Gateway, Amazon Simple Queue Service (SQS), Data Pipelines, Serverless Computing, Amazon Redshift, Web Api, Agent2Agent Protocol - **Published:** October 22, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pthn39sfgq ## About the Role * 5+ years of professional software development experience, including ownership of complex production systems. * Strong backend engineering experience with Node.js and TypeScript, including designing and building REST and/or GraphQL APIs, third-party integrations, and asynchronous processing workflows. * Experience building serverless and event-driven systems on AWS, using services such as Lambda, SQS, EventBridge, S3, and API Gateway. * Strong knowledge of relational databases, data modeling, transactions, and query optimization, ideally with PostgreSQL and/or SQL Server. * Experience building distributed or data-intensive systems that reliably process large volumes of data. * Experience designing APIs or tools for machine-to-machine or AI-agent use, including structured contracts, permissions, validation, idempotency, and predictable error handling, along with familiarity with AI agents, tool calling, MCP, A2A, or similar agent interoperability patterns. * Strong understanding of authentication, authorization, secrets management, rate limiting, retries, failure recovery, and secure API design. * Strong understanding of automated testing, CI/CD, observability, monitoring, and production operations. * Strong problem-solving and troubleshooting skills, with the ability to independently own features and services from technical discovery and design through production rollout, and to make pragmatic architectural decisions that balance scalability, reliability, maintainability, and delivery speed. * Strong communication skills and the ability to collaborate effectively across Engineering, Product, Data Science, ML, QA, and DevOps, with Upper-Intermediate or higher English proficiency, both written and spoken. Nice To Have * Experience working with AI/ML-powered systems or LLM-based applications, including production use of model or inference outputs. * Experience building AI agents or agent-ready APIs, with familiarity with MCP, A2A, tool calling, structured schemas, and agent frameworks such as LangGraph, CrewAI, or Strands Agents. * Experience with Python for backend development, data processing, automation, or AI/ML integrations. * Experience with data-intensive systems and technologies such as Redshift, Parquet, ETL/data pipelines, batch processing, or cross-cloud data flows. * Experience with GCP or building integrations and data flows across AWS and GCP. * Full-stack development experience with React and TypeScript. * Experience with large-scale content or media processing, social platform integrations, content moderation, Trust & Safety, or Brand Safety systems. ## Description We are looking for a Senior Software Engineer - Brand Safety & Agentic AI to join our Safety & Compliance team and help build and evolve CreatorIQ's AI-driven brand safety platform. This is a backend-focused role responsible for developing scalable services, APIs, and data-processing capabilities that power brand safety workflows across large volumes of creator and social content. SafeIQ helps brands identify potential risks, assess suitability, and make better-informed brand safety decisions. The system supports historical analysis, pre-campaign evaluation, and ongoing monitoring while keeping humans in control of final review and decision-making. You will work with event-driven and serverless architectures on AWS, large-scale data pipelines, transactional databases, AI/ML processing systems, AI agents, and agent-ready APIs. The ideal candidate is a strong backend engineer with experience building distributed, data-intensive systems. Full-stack experience is a strong plus. In This Role, You'll Get To * Design, build, and operate scalable backend services and APIs that power CreatorIQ's Brand Safety and Safety & Compliance capabilities. * Build and evolve event-driven and serverless systems using Node.js, TypeScript, AWS Lambda, SQS, EventBridge, S3, and related AWS services, with robust asynchronous workflows that handle retries, failures, duplicate processing, concurrency, throughput, and data consistency. * Design and operate large-scale data pipelines that ingest, process, validate, and persist creator and social content across multiple systems. * Build reliable backend workflows that integrate AI/ML and multimodal inference into customer-facing Brand Safety experiences. * Design agent-ready APIs and tools that expose Brand Safety capabilities to AI agents through clear contracts, permissions, validation, idempotency, and predictable error handling, and build and operate AI agents as services that integrate with other agents and systems through A2A, MCP, and similar interoperability patterns. * Improve data models, queries, transactional workflows, and performance across relational databases including AWS Aurora PostgreSQL and AWS RDS SQL Server, and integrate with external APIs, social platforms, cloud services, and data-processing systems across AWS and GCP. * Improve observability, monitoring, alerting, performance, scalability, and production reliability across Brand Safety services and data pipelines. * Collaborate closely with Product, Data Science, ML, QA, DevOps, and engineering teams to turn product and AI capabilities into reliable production systems. * Contribute to technical design and architectural decisions, review code, mentor engineers, and help establish engineering best practices, using AI-assisted development tools to improve development velocity, code quality, testing, and engineering workflows.