Senior Software Product Engineer- Agentic AI

About the Role:

We are seeking an experienced Agentic Engineer to develop, deploy, and optimize AI agent systems within DXG FCC CT. CT Corp is the global leader of legal entity management, corporate compliance and due diligence solutions. The ideal candidate will have deep expertise in autonomous AI systems, multi-agent architectures, and the practical implementation of agentic workflows that can operate independently to achieve complex business objectives.

Responsibilities:

• Design and implement sophisticated AI agent systems capable of autonomous decision-making and task execution

• Develop multi-agent architectures that can collaborate, coordinate, and communicate effectively

• Create agent orchestration frameworks for complex workflow automation

• Build robust agent memory systems, including episodic, semantic, and procedural memory components

• Integrate AI agents with existing business systems, APIs, and databases

• Implement agent monitoring, logging, and performance tracking systems

• Deploy agents across various environments (cloud, on-premises, edge)

• Ensure seamless handoffs between human users and autonomous agents

• Fine-tune agent behavior through reinforcement learning and feedback mechanisms

• Implement safety measures, guardrails, and fail-safe mechanisms for agent operations

• Conduct agent alignment research to ensure output matches intended objectives

• Monitor and mitigate potential risks associated with autonomous agent behavior

• Stay current with the latest developments in agentic AI, LLM capabilities, and autonomous systems

• Experiment with cutting-edge agent frameworks and methodologies

• Contribute to the development of proprietary agent technologies and IP

• Collaborate with research teams on advancing the state of agentic AI

Skills:

• Software Engineering: The ability to design, develop, and maintain software systems and applications by applying principles and techniques of computer science, engineering, and mathematical analysis. This includes the capacity to understand user requirements, create and test the software, and resolve any software-related issues.

• Software Development: The ability to design, write, test, and implement software programs, applications, and systems. This includes understanding various programming languages, software architecture, and software testing methods. It also involves problem-solving capabilities to fix software issues and improve functionality.

• Programming: The ability to design, write, test, debug, and maintain the instructions, also known as code, that a computer must follow to execute a task. This skill often involves various programming languages such as Python, TypeScript, Java, or C++.

• Problem Solving: The ability to understand a complex situation or issue and devise a solution by defining the problem, identifying potential strategies, and ultimately choosing and implementing the most effective course of action.

• Analysis: The ability to examine complex situations or problems, break them down into smaller parts, and understand how these parts work together.

• Agile: The ability to swiftly and effectively respond to changes, with an emphasis on continuous improvement and flexibility. In the context of project management, it denotes a methodology that promotes adaptive planning and encourages rapid and flexible responses to changes.

• AI Literacy: The ability to leverage and maximize the value out of the various Large Language Models (GPT-4, Claude, Gemini, open-source alternatives) and Agent frameworks and orchestration platforms being used in the industry today through effective techniques as prompt engineering, few shot prompting and chain of thought amongst other areas.

• Collaboration: Work closely with product managers to translate business requirements into agent capabilities and collaborate with data scientists on training and fine-tuning agent models

• Application Security Principles: The ability to understand and implement the principles and practices required to secure any application. This involves applying security controls to prevent, detect, and respond to vulnerabilities that might occur in different application software. Knowledge about secure coding, encryption, access control, authentication, and security testing are essential aspects of this skill.

• Public Cloud Architecture and Services: The ability to design, manage, and understand public cloud platforms and their services. This includes comprehension of service models, deployment models, and key cloud principles. This skill also involves implementing and managing the storage, compute, and networking capabilities of popular public cloud providers like AWS, Google Cloud, and Azure.

Qualifications:

• 3+ years of experience working with AI agents, autonomous systems, or related technologies

• Proficiency in Python, with experience in agent frameworks (AutoGPT, LangChain, CrewAI, etc.)

• Strong understanding of large language models (LLMs) and their integration into agentic systems

• Experience with reinforcement learning, multi-agent systems, and distributed computing

• Knowledge of API integration, microservices architecture, and cloud platforms

• Deep understanding of prompt engineering, few-shot learning, and chain-of-thought reasoning

• Experience with vector databases, embeddings, and retrieval-augmented generation (RAG)

• Familiarity with agent planning algorithms, goal decomposition, and task scheduling

• Understanding of AI safety principles and alignment techniques

• Strong software engineering fundamentals with experience in production environments

• Proficiency with version control, CI/CD, and collaborative development workflows

• Experience with containerization (Docker, Kubernetes) and cloud deployment

• Knowledge of monitoring and observability tools for distributed systems

Preferred Qualifications

• Advanced degree in Computer Science, AI, Robotics, or related field

• Experience with specific agent platforms (Microsoft Semantic Kernel, OpenAI Assistants API, Anthropic Claude, etc.)

• Background in cognitive science, psychology, or human-computer interaction

• Experience with edge computing and real-time agent deployment

• Publications or contributions to open-source agent frameworks

• Experience in regulated industries requiring explainable and auditable AI systems

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.

Compensation: