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Senior Backend/LLM Ops Engineer Closed

Job Description

Sr Backend/LLM Ops Engineer Role at Fuse Finance

Fuse is a high-growth New York City startup revolutionizing financial services infrastructure through an innovative low-code tool. Backed by top-tier venture capital, the company is creating a transformative self-service platform for configuration, integration, and automation in financial technology. We are now expanding our capabilities to leverage artificial intelligence in revolutionizing how financial services workflows and integrations are built.

Position Overview

We are seeking a Senior Backend engineer with hands-on experience with LLM ops to spearhead our artificial intelligence agents initiatives, focusing on leveraging generative AI to enhance our low-code platform capabilities. This role combines deep technical expertise in Backend development with practical experience in implementing AI agents solutions, particularly in generating and optimizing low-code workflows, user interfaces, and data schemas.

Key Responsibilities

The Senior Backend/LLM ops Engineer will drive the development and implementation of AI-powered features across our platform. Core responsibilities include:

  • Building and optimizing AI agent pipelines that leverage leading language models and AI services to enhance our low-code platform capabilities.

  • Developing sophisticated agentic workflows to ensure high-quality answers of our AI systems, with a particular focus on domain knowledge from low-code data sources.

  • Designing and implementing AI agent systems that can effectively generate and validate use case specific workflows, user interfaces, and data schemas.

  • Creating robust evaluation frameworks to measure and improve the quality of AI-generated outputs within our platform.

  • Collaborating with product and engineering teams to seamlessly integrate AI capabilities into our existing platform architecture.

  • Establishing best practices for AI implementation, including monitoring, versioning, and continuous improvement of models.

Essential Qualifications

  • Advanced degree in Computer Science or related field, with 8+ years of relevant experience in Backend Development and proven hands-on experience implementing AI agents workflows.

  • TypeScript, NodeJS.

  • Large Language Model integration (GPT, Claude, Gemini, Grok) and prompt engineering

  • AI agents evaluation.

  • Ai agents workflows pipeline design and implementation.

  • Git version control and prompt versioning management.

  • Cloud-based AI SDKs (GPT, Claude, Gemini, Grok)

  • RESTful API design principles

  • Database models designs.

  • Architectural patterns.

  • Basic understanding of concepts related to authorization and authentication within an AI agents environment.

  • Proven track record of implementing production-grade AI systems that deliver measurable business value.

Technical Expertise

Strong foundation in:

  • Large Language Processing and Language Model (LLM)

  • Machine Learning Operations (LLMOps)

  • Agents evaluation and optimization (deepchecks, openAI Evals, Langsmith and similar)

  • Cloud computing platforms (preferably AWS)

  • SQL querying and optimization.

  • ETL processing and integration..

  • RESTful API integration, management and design.

  • Software development best practices

Project Experience Requirements

Previous success in:

  • Implementing and fine-tuning large language models

  • Building agentic centered workflow pipelines.

  • Developing generative AI applications.

  • Creating automated testing and validation frameworks for AI systems.

  • Documentation and knowledge sharing of AI agents systems.

Ideal Characteristics

The ideal candidate will demonstrate:

  • Innovation in applying AI to solve complex business problems

  • Strong analytical and problem-solving abilities

  • Excellence in technical communication

  • Ability to balance technical depth with practical implementation

  • Enthusiasm for low-code platforms and their potential

  • Commitment to ethical AI development practices

Technical Environment

  • Languages: Typescript/Node.js

  • AI/ML Frameworks (Like Lanchain, LlamaIndex, Haystack, FlowWise)

  • Cloud Infrastructure: AWS

  • PostgreSQL.

  • Version Control: Git

  • CI/CD: GitHub Actions

Nice to have

  • Python and its ML/AI ecosystem (PyTorch, TensorFlow, Pandas or similar).

  • FE experience.

Impact Opportunity

This role offers the unique opportunity to:

  • Shape the future of low-code development through AI innovation

  • Build next-generation financial services automation tools

  • Work with cutting-edge AI technologies and methodologies

  • Drive technical decisions that impact product direction

  • Mentor team members in AI implementation best practices

The Selection Process

  • Silver Screening

  • Silver Technical Interview

  • Client Willo Interview

  • Client Technical Test

  • Tech Lead Interview

  • System Design Interview

  • CTO Interview

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