Sr AI Engineer I - Global Commercial Services

What You'll Do 

• Design, build, test, and operate production-grade agentic AI applications and services. 

• Contribute to the design and implementation of shared agentic AI capabilities, including: 

• Agent frameworks and orchestration 

• Planning, tool use, and memory strategies 

• Retrieval-Augmented Generation (RAG) pipelines 

• LLM integration and inference services 

• Evaluation, observability, and safety tooling 

• Partner with senior engineers to design scalable, reliable, and maintainable distributed systems. 

• Participate in technical design discussions and code reviews, helping improve engineering quality across the team. 

• Collaborate with Product, UX, and cross-functional partners to deliver AI-powered capabilities from concept through production. 

• Evaluate emerging AI technologies and help incorporate practical improvements into our platform. 

• Mentor junior engineers and contribute to a collaborative engineering culture. 

Technical Environment 

We don't hire to a narrow checklist, but successful candidates should be comfortable working in a modern, cloud-native engineering environment with an emphasis on agentic AI. 

Core Engineering Stack 

• Languages: Go, TypeScript, Python 

• APIs: REST, gRPC, and tRPC 

• Cloud: AWS and/or GCP 

• SNS, SQS, Lambda, EKS, API Gateway 

• Kubernetes 

• Distributed systems and event-driven architectures (Kafka) 

• Durable Execution frameworks, like Temporal or DBOS 

• Orchestration frameworks such as LangGraph, LangChain, Airflow, or similar 

Agentic AI and ML 

• Integrating commercial and open-source LLMs into production applications 

• Agent and orchestration frameworks such as VercelAI SDK,  LangChain, LangGraph, LlamaIndex, etc.  

• Retrieval-Augmented Generation (RAG) architectures 

• Embedding Models and Vector Databases 

• Multi-agent orchestration and agent harness development 

• Prompt engineering and structured output generation 

• Model serving, embeddings, and inference tooling  

• Familiarity with Effect TS library 

• Schema validation and state management using tools such as Zod (TypeScript) 

•  Emphasize evaluation, observability, safety, and reliability to support AI solutions deployed in a regulated, customer-facing environment. 

What We're Looking For 

• 6+ years of experience building large-scale backend or distributed software systems. 

• Experience developing AI-powered applications using LLMs, agentic workflows, RAG, or modern ML platforms. 

• Experience building production services using TypeScript, Go, Python or similar languages. 

• Strong software engineering fundamentals across backend development, APIs, cloud infrastructure, and distributed systems. 

• Familiarity with cloud platforms, containers, and Kubernetes. 

• Experience with asynchronous processing, workflow engines, queues, or streaming systems. 

• Strong problem-solving skills and the ability to work through ambiguous technical challenges. 

• Excellent collaboration and communication skills, with the ability to work effectively across engineering and product teams. 

• Passion for learning new technologies and contributing to engineering best practices. 

Preferred Qualifications 

• Experience building AI applications in financial services or other regulated industries. 

• Experience deploying production LLM or RAG-based systems. 

• Familiarity with evaluation frameworks, observability, and AI safety practices. 

• Contributions to open-source software or AI-related projects. 

• Experience with fine-tuning, model optimization, or inference pipelines is a plus.