Senior Agentic AI Engineer

Role & responsibilities:

• Design and implement agentic AI systems that automate discovery, assessment, and migration of legacy applications.
• Develop intelligent workflows for refactoring monolithic systems into microservices or serverless architectures.
• Integrate AI agents with cloud platforms (Azure, AWS, GCP) to orchestrate infrastructure provisioning, data migration, and validation.
• Build reasoning engines that optimize migration paths based on cost, performance, and compliance.
• Collaborate with architects, DevOps, and business stakeholders to align AI-driven modernization with enterprise goals.
• Concentrateson building and integrating custom AI agents to solve specific, tactical customer problems.
• Apply LLMs, graph reasoning, and planning to accelerate decision-making in migration scenarios.
• Monitor agent performance, retrain models, and continuously improve autonomy and reliability.
• Evaluate the effectiveness of prototypical agents through an understanding of both legacy and modern application development languages.

Required Skills & Qualifications:

• Bachelors or masters degree in computer science, AI, or related field.
• Experience in AI engineering, with a focus on agentic systems or autonomous workflows.
• 10+ years of experience in application development.
• Deep understanding of application migration strategies (rehost, replatform, refactor, retire).
• Experience having built and leveraged AI for software development.
• Proficiency in cloud-native development and infrastructure-as-code (Terraform, Pulumi).
• Experience building autonomous agents using frameworks like Lang Chain, Semantic Kernel, or custom planners.
• Experience with LLMs, reinforcement learning, or multi-agent systems.
• Strong programming skills in Python, Java, or other modern languages.

Preferred Qualifications:

• Experience with both modern and legacy application development.
• Experience in Legacy modernization assessments.
• Good understanding of Legacy technologies (AS400, IBM Mainframe, HP Tandem, etc)
• Experience in reverse engineering of legacy source to generate business requirements
• Certifications in cloud architecture (e.g., Azure Architect Expert, AWS Solutions Architect), Agentic AI.
• Familiarity with enterprise platforms (SAP, Infor, Oracle) and legacy modernization tools.
• Experience developing ML Models
• Knowledge of data lake architectures and ETL pipelines (e.g., Azure Data Factory, Databricks).
• Exposure to compliance frameworks (GDPR, HIPAA) and secure migration practices.