> Markdown version of [/jobs/ext/1469990-software-engineer-full-stack-ai](https://www.wearedevelopers.com/jobs/ext/1469990-software-engineer-full-stack-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer, Full Stack - AI - **Company:** Fitch Group, Inc. - **Location:** United States - **Experience:** Expert - **Salary:** $150,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Airflow, Amazon Web Services, Applications Architecture, Microsoft Azure, Cloud Computing, Cloud Engineering, Continuous Integration, Data Architecture, Data Infrastructure, Data Transformation, Decision Support Systems, Memory Management, Python (Programming Language), Software Architecture, Tensorflow, Software Engineering, SQL Databases, Data Streaming, TypeScript, Web Applications, Workflow Management Systems, Data Logging, Data Processing, Cloud Platform System, Feature Engineering, Pytorch, ReactJS, Large Language Models, Snowflake, Generative AI, Backend, Fastapi, Data Layers, Build Management, AI Platforms, Machine Learning Operations, Front End Software Development, Data Pipelines, Devsecops, Databricks - **Published:** July 28, 2026 - **Apply:** https://www.dice.com/job-detail/4b09a9d6-ef50-4e77-ad52-d5f39e7f3ab2 ## About the Role * 7+ years of experience designing and developing distributed application architecture of moderate-to-high complexity. * 3+ years in software engineering or applied ML building real-world AI/ML systems; strong Python proficiency and backend development expertise * Hands-on experience building GenAI apps with LangChain and LangGraph, including agent design, state/memory management, and graph-based orchestration. * Proficiency in ML/NLP and generative models; experience with embeddings, vector stores, RAG, and LLM integration/fine-tuning (OpenAI, LLaMA, Cohere, etc.) * Strong coding in Python and experience with frameworks/tools such as FastAPI, PyTorch/TensorFlow, MLflow; * 3-5+ years of experience in designing and developing scalable web applications using modern front-end frameworks such as React/TypeScript. * Hands-on experience with modern data platforms and cloud environments (e.g., Snowflake, Databricks, AWS and/or Azure). * Experience building and operating data pipelines, including batch and streaming patterns, with orchestration tools such as Airflow, ADF, or Dagster. * Experience working in high-performance teams using Agile methodologies. * Experience with CI/CD concepts and implementing build and deployment pipelines incorporating Security, Automation and Quality (DevSecOps). * Familiarity with modern data architecture and engineering technologies * Excellent communication skills with ability to articulate ideas clearly and concisely. ## Description We are seeking a Full Stack Software Engineer to design, build, and scale AI-enabled products that integrate Large Language Models (LLMs) into core business workflows. This role is focused on end-to-end product development-from frontend experiences to backend services and AI integrations-delivering secure, scalable, and production-grade solutions.You will work closely with Product, Design, Platform, and Data/AI partners to turn complex requirements into reliable, high-impact software. What We Offer: Opportunity to work on AI-first product development, embedding LLM capabilities into real-world applications Ownership of full-stack delivery in a modern, cloud-native engineering environment Collaboration with senior engineers, architects, and AI platform teams Exposure to internal AI platforms, agentic frameworks, and GenAI enablement initiatives Strong engineering culture emphasizing design quality, scalability, and operational excellence We'll Count on You To: Full Stack Product Development * Design, develop, and maintain end-to-end web applications, including frontend UI, backend services, and data layers * Build scalable, well-structured APIs and service integrations * Translate product and business requirements into high-quality technical solutions * Contribute to system design discussions and architectural decisions * Build reusable data transformation logic using SQL and Python, and partner with analytics and product teams to deliver business-ready datasets. * Own features through the full development lifecycle: design ? build ? deploy ? operate AI / LLM Feature Engineering * Develop and integrate LLM-powered capabilities such as chat interfaces, content generation, summarization, or decision support * Implement retrieval-augmented generation (RAG) and context management patterns where applicable * Work with internal AI platforms or approved LLM APIs to ensure consistency and compliance * Optimize LLM usage for latency, cost, and quality tradeoffs * Collaborate with AI platform teams on model integration patterns and best practices Cloud & Platform Engineering * Deploy and operate services in cloud environments using modern DevOps practices * Implement observability (logging, metrics, tracing) to ensure production reliability * Improve performance, scalability, and resilience of existing systems * Participate in incident resolution and root-cause analysis for production issues Secure & Governed Development * Build AI-enabled features that comply with internal security, data handling, and AI governance standards * Contribute required technical documentation for AI-enabled systems * Ensure responsible use of LLMs, especially when handling proprietary or sensitive data ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Building AI Applications with LangChain and Node.js](https://www.wearedevelopers.com/videos/1512-building-ai-applications-with-langchain-and-node-js) - [Intro to FastAPI](https://www.wearedevelopers.com/videos/462-intro-to-fastapi) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai)