Jobs at Pulsora

The AI Engineer will design and develop applications using LLMs, implement multi-agent workflows, optimize RAG pipelines, and contribute to full-stack development, collaborating with teams across regions.

The role involves building AI-powered products, designing reliable LLM-powered systems, and ensuring performance and quality. You'll collaborate in fast-paced environments and own the full product lifecycle.

Lead AI-powered sustainability engagements delivering audit-ready GHG inventories, Scope 1-3 calculations, decarbonization planning, and regulatory-ready reporting. Advise executives and auditors, validate AI outputs, analyze ERP and operational datasets, and improve AI models and prompts for consistent, defensible sustainability outcomes.

Lead delivery of AI-assisted sustainability services including GHG inventories, Scope 1-3 calculations, audit-ready reporting, decarbonization planning, and regulatory readiness. Advise executives and auditors, analyze ERP and operational data, validate AI outputs, and continuously improve AI models and processes for defensible sustainability outcomes.

Lead product quality across the SDLC by reducing defects, driving root-cause analysis, defining automation strategy and quality gates, building automated test frameworks (Playwright, API, integration, performance), integrating tests into CI/CD, enforcing release readiness, and using Claude Code and other AI tools to analyze issues and improve engineering outcomes.

The Applied AI Engineer will design, develop, and deploy LLM-powered applications, manage full product lifecycles, and ensure system reliability while utilizing AI-first workflows and collaborating with diverse teams.

This role involves developing and optimizing LLM applications, architecting workflows, and integrating AI functionalities. Strong experience in AI/ML and collaboration is required.

The AI Engineer will design and deploy LLM applications, optimize workflows, manage RAG systems, and perform full-stack development involving Python and Java.

The role involves building and scaling LLM-powered applications, managing the full product lifecycle, ensuring system reliability, and collaborating across teams to deliver impactful AI-driven features.

Customer-facing technical role deploying AI-enabled solutions into enterprise environments: prototype, integrate, configure, and deliver AI-native workflows, ETL pipelines, dashboards, and tooling to improve ESG reporting, automation, and operational efficiency.