pulsESG

QA Engineer

• Analyze Jira issues, incidents, support tickets, and production defects
• Use AI to trace issues to root causes in the codebase
• Review pull requests and production code using AI
• Identify recurring defect patterns
• Build defect taxonomies
• Recommend architectural improvements
• Identify technical debt
• Improve engineering practices
• Build engineering quality dashboards
• Create AI workflows that improve engineering effectiveness
• Generate Playwright tests using AI
• Review AI-generated tests
• Improve automation quality
• Generate API tests
• Generate integration tests
• Generate regression tests
• Generate edge-case tests
• Analyze production incidents and automatically generate regression tests
• Integrate automation into CI/CD
• Improve automation coverage across engineering teams
• Lead engineering teams to build quality into every release
• Coach developers on engineering best practices
• Coach QA engineers on AI-assisted automation
• Drive engineering accountability
• Conduct root cause reviews
• Challenge poor engineering practices
• Improve release readiness
• Define engineering standards
• Improve engineering quality metrics
• Drive measurable reductions in production defects
• Analyze escaped defects
• Identify recurring engineering issues
• Define corrective actions
• Define preventive actions
• Improve engineering processes
• Improve code review quality
• Improve release quality
• Reduce customer-reported defects
• Improve engineering productivity using AI

Engineering Quality Lead – AI, Product Quality

AI Engineer

• Design, develop, and deploy production-grade applications leveraging various LLMs, context optimization, etc.
• Architect and implement sophisticated, multi-step and multi-agent workflows using frameworks like LangChain and LangGraph.
• Build and optimize RAG pipelines, including implementing and managing embeddings, vector databases, and advanced rerankers to enhance response quality and relevance.
• Use code generation applications (e.g. Replit, Cursor, Google AI Studio, Git Hub Copilot in Agent mode, etc.) to create full applications (including frontend and backend), generate tests, perform testing and integrate them in the core product without writing any code.
• Lead efforts in LLM fine-tuning (e.g., LoRA, QLoRA) for specific domain knowledge and tasks, and implement strategies for efficiency.
• Develop and refine advanced prompt engineering techniques to maximize model performance, consistency, and safety.
• Own end-to-end implementation from frontend to the backend.
• Expose AI/LLM functionality written in Python using Java services, leverage multi-threading capabilities in Java to augment AI/LLM functionality developed in Python
• Utilize AI-powered development tools (e.g., GitHub Copilot, etc.) to efficiently generate, refactor, and optimize high-quality code.
• Work closely with team leads managers, QA, product managers and team in the US (this will require the willingness to partially work US working hours)

Engineer

• Lead complex enterprise deployments and implementations of the Pulsora platform for global customers
• Partner directly with customer stakeholders to understand business processes, technical requirements, and ESG reporting workflows
• Design and implement AI-enabled solutions that improve automation, compliance, reporting, and operational efficiency
• Use AI-first engineering practices including AI coding assistants, prompt engineering, rapid prototyping, vibe coding, and LLM-powered application development
• Rapidly build proofs-of-concept, internal tools, automations, integrations, dashboards, and lightweight applications
• Configure workflows, validations, ETL pipelines, analytics, integrations, and reporting within the Pulsora platform
• Develop reusable implementation accelerators and AI-powered tooling that improve delivery speed and scalability
• Collaborate closely with Engineering and Product teams to influence roadmap priorities based on customer feedback
• Lead solution workshops, architecture reviews, product demonstrations, and technical deep dives
• Troubleshoot technical escalations and serve as a trusted technical advisor to enterprise customers
• Support customer adoption, quarterly business reviews, and annual reporting cycles

pulsESG

Engineering Quality Lead – AI, Product Quality

AI Engineer

Forward Deployed Engineer

Forward Deployed Engineer