Senior Software Engineer, AI Infra & Platform

This role is open to Senior to Principal Level

ABOUT THE ROLE

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.

WHAT YOU'LL DO

• Design and implement platforms for LLM orchestration, tool execution, and agent workflows; develop shared services and abstractions used across multiple AI applications

• Build 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 actions

• Build reusable, composable abstractions for safe and scalable tool usage; ensure all tools are reliable, observable, and secure when interacting with sensitive data

• Build infrastructure for multi-step agentic systems: state management, tool routing, retries, failure handling, and reusable orchestration patterns

• Develop evaluation frameworks and observability tooling — logging, tracing, and monitoring for model behavior and system performance

• Design for high availability, fault tolerance, and graceful degradation; optimize for latency, throughput, and cost across AI workloads

• Build scalable RAG pipelines, indexing systems, and data processing workflows for large-scale structured and unstructured data

• Create internal tools, SDKs, and platforms that enable engineers to integrate AI capabilities quickly and safely; standardize best practices around prompting, evaluation, and deployment

• Partner with AI Applications engineers to support production use cases and translate product needs into scalable infrastructure solutions

REQUIREMENTS

• Degree in Computer Science, Engineering, or a related quantitative field, or equivalent practical experience

• Strong software engineering fundamentals: system design, distributed systems, and maintainable code

• Proven track record building and operating production systems at scale

• Proficiency in Python and TypeScript; comfortable working across a polyglot stack

• Experience building backend systems, APIs, or infrastructure platforms

• Experience with AI/ML systems in production, including LLM integrations or data pipelines

• Experience designing or integrating systems with tool or skill abstractions — e.g. function calling, APIs, or capability layers used by AI systems

• Ability to operate with high ownership in ambiguous, fast-moving environments

PREFERRED QUALIFICATIONS

• Experience building AI platforms or infrastructure layers, not just AI applications

• Hands-on experience with RAG systems and vector databases such as Pinecone, Weaviate, or pgvector

• Experience with agent orchestration frameworks such as LangGraph, LangChain, or custom-built systems

• Experience with evaluation and observability tooling for AI systems

• Cloud infrastructure experience — GCP (Cloud Run), AWS (ECS, Lambda), containerized or serverless deployments

• Experience with event-driven systems, queues, and async processing; MLOps and CI/CD pipelines

• Background in regulated domains such as FinTech, LegalTech, or HealthTech

• Familiarity with data privacy and security techniques including PII handling and redaction