Senior Solutions Architect

Kforce has a client that is seeking a Senior Solutions Architect in Chicago, IL. Responsibilities:

• Own the end-to-end technical design of LLM and AI platform capabilities, including new solutions and enhancements to existing systems
• Translate product and business requirements into clear solution designs, technical plans, and development tasks
• Make and document architecture decisions, technical tradeoffs, integration patterns, and engineering standards
• Provide technical direction to engineers, remove technical blockers, and ensure alignment across application, data, cloud, security, and platform teams
• Design, develop, and maintain scalable Python services, APIs, and microservices using FastAPI or Flask
• Contribute directly to complex or foundational code and lead code reviews to ensure quality, security, maintainability, and performance
• Define reusable development patterns, testing practices, API standards, and documentation expectations for the team
• Lead the design and implementation of LLM applications, LangChain workflows, and Retrieval-Augmented Generation (RAG) pipelines
• Guide model, prompt, embedding, chunking, retrieval, re-ranking, and evaluation strategies based on use-case requirements
• Architect and optimize vector-store solutions using technologies such as Pinecone, Chroma, FAISS, or Milvus
• Establish evaluation and monitoring approaches for response quality, relevance, latency, reliability, safety, and cost
• Design and oversee deployment of secure, scalable, and resilient AI services on AWS using services such as Lambda, EC2, S3, EKS, and RDS
• Partner with DevOps and MLOps teams to implement CI/CD, infrastructure automation, observability, incident response, and production support practices
• Ensure solutions meet enterprise requirements for availability, fault tolerance, security, governance, scalability, and operational readiness
• Extensive software engineering experience, including experience serving as a Technical Lead, Lead Engineer, or Senior Engineer responsible for technical direction
• Demonstrated experience architecting and delivering production LLM or generative AI applications, including RAG-based solutions
• Experience with LLM platforms and frameworks such as OpenAI, Anthropic, Hugging Face Transformers, or LangChain
• Experience designing and deploying secure, scalable services in AWS cloud environments
• Experience leading design reviews, code reviews, technical planning, and resolution of complex engineering issues
• Strong understanding of LLM application architecture, prompt engineering, embeddings, vector databases, retrieval mechanisms, re-ranking, and evaluation
• Strong hands-on proficiency in Python and backend development using FastAPI, Flask, or comparable frameworks
• Ability to mentor engineers and influence technical decisions without relying on formal people-management authority
• Strong written and verbal communication skills, including the ability to explain architecture decisions and tradeoffs to technical and non-technical audiences
• Professional English proficiency and ability to collaborate effectively during agreed-upon U.S. business-hour overlap