Software Engineering, Full Stack - AI

Fitch Group•Chicago, IL

6d•$135,000 - $145,000•Onsite

About The Position

Fitch Group is seeking a Full Stack-AI Engineer to join their External Application Development Chapter in Chicago. This role is part of a talented, agile team focused on building cloud-native applications, including data ingestion pipelines, microservices, data visualizations, and customer-facing web products using modern front-end technologies. The position offers an innovative technological environment with a modern, cloud-based, containerized, serverless, and microservices-oriented technology stack. It provides high impact and visibility, allowing the engineer to lead and shape data engineering and API initiatives that directly affect customer-facing products and backend systems. The role also emphasizes professional growth and development, with opportunities to mentor a team and expand personal skills in emerging technologies, all within a supportive and collaborative agile work environment.

Requirements

7+ years of experience designing and developing distributed application architecture of moderate-to-high complexity.
7+ years of software engineering experience, with strong backend development expertise in Java and Python.
Strong hands-on experience building scalable backend services using technologies such as Spring Boot, Fast API, or similar frameworks.
5+ years of experience designing and developing scalable web applications using modern front-end frameworks such as React, TypeScript.
Proven experience building and supporting microservices-based architectures in cloud-native environments.
Hands-on experience designing and deploying AI/ML solutions in production.
Strong knowledge of generative AI concepts, including experience with embeddings, vector stores, RAG, and LLM integration.
Experience building GenAI applications using tools and frameworks such as LangChain, LangGraph, and leading LLM providers or open-source models.
Experience with relational databases such as Oracle or PostgreSQL, and familiarity with NoSQL and search technologies such as MongoDB, DynamoDB, Elasticsearch, or Solr.
Expertise in modern package management, test frameworks (e.g., NPM, Yarn, Webpack, Jest, Enzyme, Karma, Jasmine, Mocha, Wraith), CI/CD pipelines using GIT and modern DevSecOps practices, including automation, testing, and secure software delivery.
Experience working in high-performance teams using Agile methodologies.
Strong communication and collaboration skills, with the ability to clearly articulate technical concepts to both technical and non-technical stakeholders.

Nice To Haves

Experience building AI-enabled features for customer-facing enterprise applications.
Exposure to AWS services such as EC2, S3, Route 53, CloudFront, CloudFormation, and networking concepts such as VPCs, subnets, and security groups.
Experience with containerization and container orchestration technologies.
Familiarity with data engineering and modern data architecture patterns.
Experience with observability, monitoring, and production support for distributed systems.
Familiarity with Atlassian tools such as JIRA, Confluence, Bitbucket, and Bamboo.
Experience mentoring engineers and influencing technical standards across teams.
Exposure to business intelligence or data visualization tools.

Responsibilities

Demonstrate technical expertise in full-stack technologies, AI-enabled solutions for enterprise-scale applications and applications.
Demonstrate technical experience in design best practices, build modern AI/ML solutions, including generative AI/LLM-based applications aligned to business and product outcomes, providing effective translation to code artifacts, and implementing an appropriate integration approach for API/data layer.
Contribute to and guide the development of GenAI applications using frameworks such as LangChain and LangGraph, including agent workflows, memory/state handling, and graph-based orchestration.
Work as part of an agile team in design, development, debugging, and deployment efforts while addressing security, cross-browser, and cross-platform expectations and concerns.
Collaborate with Product Owners and stakeholders to understand business needs, define and develop applications/architecture, design, review, implement, and optimize Engineering processes.
Build data expertise and a deep understanding of business domain knowledge and own data quality for allocated areas of ownership.
Maintain and enhance microservices-based components for the application suite.
Recommend, create, and maintain development best practices and guidelines to be used across various applications.
Write automated unit, integration, performance, and visual regression test cases.
Integrate test case execution with the CI/CD pipeline to better align with the DevSecOps strategy.
Promote, implement, and evolve development best practices, especially on commits, versioning, and dependency management.