Senior Software Engineer

nsibilities

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.

Qualifications

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.