Machine Learning Software Engineer _GenAI Applications

Role & responsibilities

• Architect and develop agentic workflows enabling multi-agent orchestration across GenAI applications.

• Strong hands-on experience with Python (3.83.12), backend development, REST APIs, and Microservices.

• Experience integrating and evaluating LLMs such as GPT-4, GPT-5, Claude, and Llama using frameworks like OpenAI Responses API and LangChain.

• Expertise in Prompt Engineering, LLM optimization, analytics feedback systems, and AI-powered application development.

• Strong experience with AWS, Docker, Kubernetes, CI/CD pipelines, infrastructure as code, observability, and security best practices.

• Experience with fraud detection, intelligent automation, and conversational AI platforms.

• Exposure to multi-agent frameworks and parallel model onboarding.

• Experience with Confluence, release planning, and PR tracking systems.

• Knowledge of RBAC, audit logging, and governance controls for AI/ML systems.

• Experience with automated testing frameworks, code reviews, and beta client deployments.

Preferred candidate profile

• Design and architect agentic workflows supporting multi-agent orchestration across Experian Assistant features.

• Design, optimize, and evaluate prompts for LLM-powered solutions and analytics feedback systems.

• Integrate and evaluate LLMs including GPT-4, GPT-5, Claude, and Llama for enterprise AI use cases.

• Collaborate with engineering teams to deliver latency-optimized solutions and support parallel model onboarding.

• Ensure code quality through automated testing, peer code reviews, and CI/CD practices.

• Maintain deployment pipelines and support beta client testing, glossary expansion, and sandbox integrations.

• Contribute to deployment documentation, release planning, and knowledge management using Confluence and internal tools.

• Implement security, RBAC, audit logging, observability, and version control best practices for AI/ML solutions.