• Build AI agents, workflows, tools and automations that solve real customer, product and operations problems. • Apply LLMs, retrieval, tool calling, evaluations, guardrails and automation to practical financial workflows. • Create AI-assisted experiences for onboarding, support, KYC, risk review, CRM, operations, document handling and product intelligence. • Work with product and engineering teams to identify what is worth building, then build it quickly and improve it in production. • Design around real constraints: accuracy, hallucination risk, latency, cost, security, compliance and user trust. • Turn manual processes into reliable AI-enabled systems that can scale.

• Build AI agents, workflows, tools and automations that solve real customer, product and operations problems • Apply LLMs, retrieval, tool calling, evaluations, guardrails and automation to practical financial workflows • Create AI-assisted experiences for various operational tasks • Work with product and engineering teams to build and improve solutions • Design around real constraints

• Build AI agents, workflows, tools and automations that solve real customer, product and operations problems. • Apply LLMs, retrieval, tool calling, evaluations, guardrails and automation to practical financial workflows. • Create AI-assisted experiences for onboarding, support, KYC, risk review, CRM, operations, document handling and product intelligence. • Work with product and engineering teams to identify what is worth building, then build it quickly and improve it in production. • Design around real constraints: accuracy, hallucination risk, latency, cost, security, compliance and user trust. • Turn manual processes into reliable AI-enabled systems that can scale.

• Build AI-powered workflows, assistants, agents and automation systems. • Apply AI across customer support, CRM, onboarding, claims, renewals, payments, operations and internal tools. • Work with product and engineering teams to turn manual processes into scalable AI-native systems. • Build integrations with LLMs, internal data, APIs, documents, knowledge bases and business systems. • Design evaluation, monitoring and fallback flows so AI outputs are useful, safe and reliable. • Prototype quickly, test with users or operators, then productionize what works. • Improve speed, quality and consistency across workflows using AI where it creates real business value.