Senior Software Engineer, AI

Fitch Solutions is hiring a Senior Software Engineer, AI to develop and deploy scalable, production-grade generative AI systems and enterprise applications. The role leads AI engineering initiatives, builds cloud infrastructure and full-stack products, and partners with cross-functional teams to deliver solutions that meet business and user needs.

Finance

• FinTech
• Credit
• Financial Services
• 2 email credits available today
• Beyond your network
• Manas Angalakuduti & 4 connections
• From your previous company
• & 2 connections
• Previously@undefined and...
• from your School
• @undefined and...

Responsibilities

• 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
• 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
• Build robust production infrastructure – Develop enterprise-scale APIs (FastAPI) for deployment, architect and implement comprehensive cloud-based AI infrastructure on AWS/Azure, and ensure systems are optimized for performance, reliability, and scalability
• Demonstrate full-stack engineering excellence – Apply proficiency across the entire technology stack to build enterprise-grade websites and applications, integrating AI capabilities seamlessly into user-facing products and backend systems
• Build and deliver reliable AI solutions – Participate in the full software development lifecycle for AI initiatives, contribute technical insights to design discussions, apply engineering best practices
• 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

Benefits

• Hybrid work environment: 2 to 3 days a week in office required based on your line of business and location
• Dedicated trainings, leadership development and mentorship programs
• Retirement planning
• Financial wellness programs
• Tuition reimbursement programs
• Comprehensive healthcare offerings
• A generous global parental leave plan
• Paid volunteer days
• Support for community engagement initiatives
• Financial information services, credit ratings, research, and analytics.
• London, England, GBR
• https://www.fitch.group/
• Distribution of Different Job Fields Receiving Sponsorship
• Represents job field similar to this job
• Engineering and Development
• Management and Executive
• Human Resources
• Product Management
• Trends of Total Sponsorships
• *2026
• (17)
• 2025
• (21)
• 2024
• (5)
• 2023
• (18)
• 2022
• Late Stage

Qualifications

• 7+ years of professional experience designing, developing, and deploying production-grade AI/ML systems, with a proven track record of delivering sophisticated generative AI and machine learning solutions at scale
• 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 generative AI solutions into production environments, including working with large language models, designing multi agentic systems and embedding AI capabilities into existing product ecosystems
• Strong foundation in MLOps practices, containerization technologies (Docker, Kubernetes/AWS EKS), cloud infrastructure (AWS/Azure), AI-specific services (AWS Bedrock, SageMaker, Azure AI Search), and orchestration tools
• Excellent communication and collaboration skills, with the ability to translate complex technical concepts for diverse stakeholders and work effectively across cross-functional teams
• 7+ years of professional experience designing, developing, and deploying production-grade AI/ML systems, with a proven track record of delivering sophisticated generative AI and machine learning solutions at scale.
• 5+ years in full stack software engineering building and deploying real-world enterprise applications; advanced Python programming skills with strong backend development capabilities.

Required skills

• FastAPI, Full-Stack Software Engineering, Generative AI, LLM Integration LLaMA, LLM Integration OpenAI, LangChain and LangGraph, MLOps, Machine Learning, Model Context Protocol (MCP), PyTorch and TensorFlow, Python, Retrieval-Augmented Generation (RAG)

Experience

• 7+ years