About the position
Fitch Solutions is seeking an Engineering & Quality Software Engineer, Associate Director, AI to join their team in Chicago. Fitch Solutions is a leading provider of insights, data, and analytics for investment strategies, risk management, and strategic opportunities. As part of Fitch Group, owned by Hearst, this role will drive high-impact AI initiatives and identify cross-product synergies. The position operates in a dynamic environment that encourages innovation and collaboration to develop solutions for evolving global markets. The company offers a portfolio of best-in-class products and opportunities for career advancement within a company known for its expertise and commitment to excellence.
Responsibilities
- Create transformative AI systems with measurable impact – Design and deploy production-ready generative AI platforms, multi-agent systems, and intelligent automation; tackle frontier AI challenges witnessing your innovations reshape products in real-time.
- Leverage cutting-edge AI innovation – Experiment with cutting-edge LLMs and foundation models, architect RAG implementations, design sophisticated agentic systems, and develop Model Context Protocol (MCP) servers for Fitch Solutions; stay at the bleeding edge of AI technology with access to the latest tools, frameworks, and platforms.
- Lead enterprise-wide AI standardization initiatives – Build GenAI solutions across multiple business units while creating unified patterns, reusable components, and standardization frameworks that enable AI at enterprise scale across Fitch Group.
- Address complex, cross-functional challenges – Work at the intersection of engineering and product development, building systems that leverage GenAI agentic workflows and production-scale deployment; tackle problems that will expand your expertise and push the boundaries of what's technically possible.
- Lead transformative GenAI system development – Spearhead the creation of sophisticated generative AI solutions including enterprise chatbot platforms, evaluation frameworks, agentic workflows, RAG architectures, applied GenAI applications, and Model Context Protocol (MCP) implementations; deliver production-grade, scalable code that meets enterprise performance standards.
- Rapidly prototype and scale innovations – Experiment with emerging capabilities, validate technical feasibility through proofs-of-concept, and scale successful experiments into enterprise-ready systems.
- Design and develop robust production infrastructure – Build enterprise-scale APIs (FastAPI), cloud-based AI infrastructure on AWS/Azure, and systems optimized for performance, reliability, and scalability.
- Pioneer AI innovation through hands-on engineering – Experiment with cutting-edge foundation models, design and implement GenAI/ML architectures, assess emerging AI technologies, develop rapid proofs-of-concept, and bridge the gap between research breakthroughs and production-ready capabilities that generate tangible business value.
- Lead technical design – Drive technical design reviews, architecture discussions, and POC evaluations; identify risks, propose solutions, and ensure successful delivery of AI initiatives.
- Champion engineering excellence and iteration– Implement robust CI/CD pipelines, define coding standards and testing strategies, and build systems that are both cutting-edge and production-reliable.
- Solve novel technical challenges – Tackle complex problems at the intersection of AI innovation and enterprise-grade engineering; balance technical debt with feature development.
- Collaborate and communicate effectively – Partner with cross-functional teams including product managers, engineers and business stakeholders to translate complex technical concepts, gather requirements, and ensure AI solutions directly address user needs and strategic objectives.
Requirements
- 9 + years of professional experience designing, developing, and deploying production-grade full stack applications.
- 5+ years in full stack software engineering building and deploying real-world enterprise applications; advanced Python programming skills with strong backend development capabilities.
- Proven experience in developing and deploying intelligent conversational AI systems using RAG architectures, Model Context Protocol (MCP), AI-enabled search, vector databases, and LLM integration in real-time enterprise environments.
- Hands-on enterprise experience developing GenAI applications using LangChain and LangGraph frameworks with expertise in agent architecture design, state management, memory systems, and graph-based workflow orchestration.
- Strong technical expertise in embeddings, vector databases for AI integration, and LLM integration/fine-tuning across platforms such as OpenAI, LLaMA; solid understanding of ML algorithms with production experience using frameworks and tools including FastAPI, PyTorch/TensorFlow, and MLflow.
- Extensive experience building and integrating