Senior AI Infra & Platform Engineer

Our client is a leading technology platform in the financial services space, combining proprietary AI, deep domain expertise, and enterprise-grade security to serve a broad range of client needs. They are trusted by some of the largest names in the industry and have been widely recognized for innovation and leadership in their category.

They are seeking a Software Engineer, AI/ML (Infrastructure & Platform) to build the foundational systems powering their next generation of AI applications. This is a systems-focused role — you will design and build the platforms, abstractions, and infrastructure that enable teams to reliably develop, deploy, and scale AI systems, including agentic workflows, retrieval pipelines, and model integrations. Your work will directly enable product teams to move faster while ensuring AI systems are reliable, observable, secure, and cost-efficient

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WHAT YOU'LL

• DODesign and implement platforms for LLM orchestration, tool execution, and agent workflows; develop shared services and abstractions used across multiple AI applicatio
• nsBuild and maintain the tools and skills that agents depend on — including APIs, workflows, and integrations — with clear interfaces for data retrieval, document processing, and external system actio
• nsBuild reusable, composable abstractions for safe and scalable tool usage; ensure all tools are reliable, observable, and secure when interacting with sensitive da
• taBuild infrastructure for multi-step agentic systems: state management, tool routing, retries, failure handling, and reusable orchestration patter
• nsDevelop evaluation frameworks and observability tooling — logging, tracing, and monitoring for model behavior and system performan
• ceDesign for high availability, fault tolerance, and graceful degradation; optimize for latency, throughput, and cost across AI workloa
• dsBuild scalable RAG pipelines, indexing systems, and data processing workflows for large-scale structured and unstructured da
• taCreate internal tools, SDKs, and platforms that enable engineers to integrate AI capabilities quickly and safely; standardize best practices around prompting, evaluation, and deployme
• ntPartner with AI Applications engineers to support production use cases and translate product needs into scalable infrastructure solutio

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REQUIREME

• NTSDegree in Computer Science, Engineering, or a related quantitative field, or equivalent practical experie
• nceStrong software engineering fundamentals: system design, distributed systems, and maintainable c
• odeProven track record building and operating production systems at sc
• aleProficiency in Python and TypeScript; comfortable working across a polyglot st
• ackExperience building backend systems, APIs, or infrastructure platfo
• rmsExperience with AI/ML systems in production, including LLM integrations or data pipeli
• nesExperience designing or integrating systems with tool or skill abstractions — e.g. function calling, APIs, or capability layers used by AI syst
• emsAbility to operate with high ownership in ambiguous, fast-moving environme

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PREFERRED QUALIFICAT

• IONSExperience building AI platforms or infrastructure layers, not just AI applicat
• ionsHands-on experience with RAG systems and vector databases such as Pinecone, Weaviate, or pgve
• ctorExperience with agent orchestration frameworks such as LangGraph, LangChain, or custom-built sys
• temsExperience with evaluation and observability tooling for AI sys
• temsCloud infrastructure experience — GCP (Cloud Run), AWS (ECS, Lambda), containerized or serverless deploym
• entsExperience with event-driven systems, queues, and async processing; MLOps and CI/CD pipel
• inesBackground in regulated domains such as FinTech, LegalTech, or Health
• TechFamiliarity with data privacy and security techniques including PII handling and redac