Senior Systems Analyst (AI/ML)

Role Summary

We are seeking a Senior Systems Analyst with strong enterprise application experience to support AI-driven modernization initiatives. The role focuses on analyzing legacy systems, enabling AI-assisted workflows, building structured knowledge models, and supporting engineering teams in transforming applications using modern AI-enabled practices.

The ideal candidate combines strong analytical skills with exposure to AI tools and modern engineering approaches.

Key Responsibilities

• Analyze legacy applications, architectures, and technical dependencies to support modernization initiatives.
• Perform reverse engineering to understand business logic, workflows, and system behaviour.
• Create and maintain structured technical documentation using AI-assisted tools.
• Model relationships between systems, APIs, data flows, and components to enable knowledge-driven engineering.
• Support development of knowledge graphs and structured repositories to improve AI accuracy and traceability.
• Collaborate with engineering teams using AI copilots and LLM tools to accelerate analysis and workflow design.
• Participate in multi-agent AI workflows and assist in defining agent roles and interactions.
• Identify potential AI hallucinations or inconsistencies and support mitigation through validation and structured inputs.
• Apply human-in-the-loop review practices to ensure quality and reliability.
• Conduct functional analysis and support parity validation between legacy and modernized systems.
• Work closely with development, QA, and DevOps teams to support testing and deployment readiness.

Required Qualifications

• 812+ years' experience in systems analysis, enterprise applications, or solution delivery.
• Experience working with legacy systems or transformation initiatives.
• Strong analytical, documentation, and stakeholder collaboration skills.

Technical Skills

• Systems Analysis
• Reverse Engineering
• Enterprise Documentation
• Knowledge Graphs / Neo4j
• KAG / RAG concepts
• LLM tools / AI Copilots
• Multi-agent workflows
• API integration
• Microservices understanding
• Cloud platforms (AWS/Azure/GCP)
• DevOps awareness
• AI governance and validation
• Programming experience (Java, Python, or similar).

Preferred Skills

• Telecom or large-scale enterprise environments.
• Workflow orchestration tools (Temporal, ServiceNow).
• Exposure to AI-driven engineering workflows.