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# Software Engineer - AI

- **Company:** WEALTH PARTNERS, LLC
- **Location:** New York, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Automated Storage and Retrieval Systems, Cloud Computing, Data Structures, Python (Programming Language), TypeScript, AI Infrastructure, Multi-Agent Systems, Information Technology, Api Design
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/senior-software-engineer-ai-wealthcom-8142058

## About the Role

* Degree in Computer Science, Engineering, or equivalent practical experience
 * Strong software engineering fundamentals (system design, data structures, clean code)
 * Proven track record of building and shipping production systems
 * Proficiency in Python and/or TypeScript. Must be comfortable working across a polyglot stack, picking up new languages and frameworks as needed
 * Experience building AI-powered applications in production
 * Hands-on experience with agentic or multi-step AI systems
 * Experience working with APIs or tool integrations within AI systems
 * Ability to operate in ambiguous, fast-moving environments

Preferred Qualifications (Bonus Points):

 * Experience building end-to-end agentic applications
 * Experience with:
 + Agent frameworks (LangGraph, LangChain, etc.)
 + Evaluation / observability systems
 + RAG systems and vector databases
 * Experience with cloud infrastructure, preferably AWS or GCP.
 * Experience in regulated domains (finance, legal, real estate, healthcare, etc.)

## Description

We are seeking a Software Engineer, AI to build the next generation of AI-powered applications. This is a builder role. You will design and ship production-grade, agentic systems that deliver real user value - not prototypes or demos., * Integrate and compose tools ("skills") such as APIs, retrieval systems, and external actions

 * Design product features that leverage these capabilities effectively within agent workflows
 * Collaborate with AI Infrastructure to improve tool interfaces and behavior

Drive quality and performance

 * Build evaluation and feedback loops
 * Implement guardrails and monitoring
 * Optimize for latency, cost, and accuracy


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