Senior Software Engineer - GenAI

Description

The Senior Software Engineer – Generative AI will lead the architecture and scaling of AI‑powered capabilities across Energy Exemplar’s simulation and planning platforms, designing reusable Agentic AI platforms that enable multiple product teams to build safe, domain‑aware AI agents aligned with energy‑market requirements.

• Architect and implement end‑to‑end Generative AI systems with advanced RAG, Agentic AI workflows, and multi‑modal orchestration across products.
• Design Agentic AI platforms supporting creation, orchestration, monitoring, evaluation, and governance of AI agents for multiple use cases.
• Define domain‑aware RAG architectures enabling AI agents to reason over energy market rules, model inputs, constraints, and simulation outputs.
• Lead development of production‑grade AI services using Python and/or .Net/Java, ensuring reliability and performance for enterprise customers.
• Create AI data pipelines leveraging Azure OpenAI, Azure AI Foundry, Azure AI Search, and Azure Storage or equivalent services.
• Establish standards for prompt management, agent memory, tool invocation, evaluation metrics, observability, and cost control.
• Collaborate with product managers, energy domain experts, and cloud teams to align AI solutions with real customer workflows.
• Mentor engineers on AI, backend, and full‑stack design best practices.
• Ensure AI solutions meet security, compliance, and responsible AI requirements for critical infrastructure software.
• Influence technical roadmap decisions related to AI platforms and capabilities.
• Stay current with advancements in Agentic AI, Azure AI services, and enterprise AI architecture patterns.

Requirements

• 5–10 years of professional software engineering experience with strong expertise in Python and/or .Net/Java.
• Proven experience delivering production Generative AI solutions, including large‑scale RAG implementations.
• Demonstrated ability to design and build Agentic AI agents and platforms.
• Deep understanding of LLMs, agent orchestration, vector search, prompt optimization, memory strategies, and evaluation frameworks.
• Hands‑on experience with cloud‑native architecture (preferably Azure), containers, and orchestration platforms.
• Solid background in distributed systems, API‑driven architectures, and product‑scale platform design.
• Experience leading technical design discussions and mentoring engineers.
• Strong debugging, performance tuning, and problem‑solving skills.
• Excellent communication skills, capable of influencing both technical and non‑technical stakeholders.
• Ability to balance innovation with engineering rigor and long‑term maintainability.

Benefits

Training + Development

Interview process

Visa Sponsorship

Security clearance