Senior Software Engineer – Marketing Technology

This is a fully remote position, open to applicants in United States.

📋 Description

• Conceptualize, create, and implement scalable multi-agent systems and orchestration layers for autonomous business planning, content generation, and execution.

• Propel prioritized enterprise AI initiatives from prototypes to stable, high-throughput production solutions.

• Incorporate model governance, observability, data protection, and ethical AI validation throughout the model lifecycle.

• Link autonomous AI agents and subagents with enterprise databases and MarTech platforms to minimize manual process friction.

• Design Retrieval-Augmented Generation pipelines, semantic caching, and vector database architectures.

• Create automated functional, regression, and destructive stress testing for non-deterministic AI outputs and multi-agent systems.

• Collaborate with internal TechOps to develop self-healing automation loops for incident detection and automated triage.

• Engage in agile processes and work with Product Teams to ensure user stories are valuable, developer-ready, clear, and testable.

• Guide junior engineers and lead technical discussions.

• Offer insights on contemporary software development frameworks and contribute to architectural design reviews.

⛳️ Requirements

• Candidate must be at least eighteen years old.

• Must have legal authorization to work in the United States.

• 3–6 years of professional experience in software engineering, with a focus on distributed systems, AI/ML application architecture, or intelligent workflow automation.

• Proficient in Python, Java, or Go.

• Practical experience in developing multi-agent systems or utilizing agent orchestration frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel.

• Strong understanding of LLMs, prompt engineering, vector databases, and embedding methodologies.

• Familiarity with AI observability and evaluation systems, including model drift, latency, costs, hallucination rates, and agent-to-agent performance metrics.

• Experience with MLOps pipelines and cloud-native AI infrastructure in AWS, GCP, or Azure.

• Knowledge of enterprise data streaming, API management, and integration layers that connect AI agents to CDPs, CRMs, and content management systems.

• Comprehension of enterprise software design patterns, microservices architecture, and Git.

• Awareness of security frameworks, ethical AI standards, data governance, privacy protection, and regulatory model compliance.

• Demonstrated ability to translate complex, ambiguous business requirements into technical architectures.

• Experience mentoring junior engineers and leading architectural design reviews across cross-functional technology teams.

• Bachelor's degree or its equivalent in a relevant field.

🏝️ Benefits

• No travel required.