We’re seeking a hands-on AI/ML engineer to design, build, and produce Generative AI solutions—including RAG pipelines and multi-agent systems—to automate workflows and drive operational excellence. You’ll work closely with solution/data architects, software developers, data engineers, and domain experts to rapidly prototype and deliver scalable, enterprise-grade systems.

This is an individual contributor role requiring strong research skills, deep expertise in AI foundation models, and the ability to translate cutting-edge concepts into impactful solutions for digital grid challenges.

A Snapshot of your Day

How You’ll Make an Impact (responsibilities of role)
- End-to-End GenAI Development: Design and implement RAG pipelines, agentic workflows, and LLM integrations for tasks such as document understanding, classification, and knowledge assistance.
- AI Enterprise Architecture: Robust Experience in AI architecture (scalable, modern, and secure) design across AI/ML enterprise solutions.
- Data & MLOps Foundations: Architect data pipelines and cloud solutions for training,



deployment, and monitoring on Azure/AWS with Docker, Kubernetes, and CI/CD.
- Rapid Prototyping to Production: Convert problem statements into prototypes, iterate with stakeholders, and harden into production-ready microservices (FastAPI) with APIs and event-driven workflows.
- Evaluation & Reliability: Define rigorous evaluation metrics for LLM/ML systems (accuracy, latency, cost, safety), optimize retrieval quality, prompt strategies, and agent policies.
- Security & Compliance: Implement Responsible AI guardrails, data privacy, PII handling, access controls, and auditability.
- Collaboration & Enablement: Partner with data engineers, mentor junior team members, and contribute to internal documentation and demos.

What You Bring (required qualification and skill sets)
- Education: Bachelor’s/master’s in computer science, Data Science, Engineering, or equivalent experience
- Experience:
- 7-12 ye

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