Peakflo

HQ
Singapore
45 Total Employees
Year Founded: 2021

Jobs at Peakflo

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Recently posted jobs

Financial Services
Serve as the primary client advocate for B2B SaaS customers: manage implementations, document AS-IS/TO-BE designs, run SIT and UAT, troubleshoot post-hypercare issues, ensure ROI delivery, and drive renewals and long-term relationships.
Financial Services
Investigate escalated production incidents (DB anomalies, failed payments, data migrations), write post-mortems and runbooks, and build AI-powered automation (LLM diagnostics, agents) plus developer tooling. Maintain CI/CD, GCP infrastructure, container deployments, observability, and partner on ERP and payment provider integrations.
Financial Services
Outbound, mid-market SDR internship focused on prospecting and cold-calling to generate qualified meetings/opportunities for Account Executives. Work North American shift remotely from India, collaborate to build sales processes, and support pipeline generation with resilience and professionalism.
Financial Services
Develop and refine voice-optimized prompts and agentic LLM workflows for finance use cases. Build RAG grounding, integrate LLMs with voice/telephony (LiveKit), implement feedback loops, A/B testing, fine-tune models, and collaborate on production ML services and OCR/chatbot components.
11 Hours AgoSaved
Remote
IN
Financial Services
Analyze operational data and processes, identify bottlenecks, design scalable solutions, automate workflows and reporting with Python and SQL, build dashboards and monitoring, perform root-cause analysis, document logic and collaborate with product, engineering, and ops teams to improve automation and data quality.
Financial Services
Build and deploy agentic finance AI solutions: design voice‑optimized prompts and conversational flows, integrate LLMs (Gemini/GPT/Claude) with RAG and enterprise data, implement voice/speech/telephony integrations, automate workflows and reporting using Python and SQL, and collaborate across product, engineering, and operations to tune and monitor production ML systems.