Senior Ai Solutions Architect

Pb Consulting; La Grange (IL); On-site; USD 140,000 - 210,000; Full time

Job summary

Pb Consulting seeks a Senior AI Solutions Architect to lead scalable Generative AI, LLM, and RAG projects. You will drive architecture, Python development, and AWS‑based production AI services, mentoring engineers and guiding best practices.

Responsibilities include end‑to‑end design, technology strategy, and collaboration with DevOps/MLOps teams to deliver secure, scalable AI solutions. Strong backend and cloud experience are required for this hands‑on leadership role.

Qualifications

• Proficient in Python and backend development with hands-on engineering leadership.
• Experience delivering production LLM–Generative AI and RAG solutions.
• Strong knowledge of LLM architecture, embeddings, and vector databases.
• Experience with OpenAI, Anthropic, Hugging Face, LangChain, or similar platforms/frameworks.
• Extensive AWS cloud architecture and deployment experience.

Responsibilities

• Own end-to-end architecture and technical design of LLM and Generative AI solutions.
• Translate business requirements into scalable architectures and plans.
• Define architecture standards, integration patterns, and engineering best practices.
• Provide technical direction and lead design and code reviews.
• Design and develop scalable Python APIs and microservices (FastAPI, Flask).
• Architect and implement LLM applications, LangChain workflows, and RAG pipelines.
• Define strategies for prompt engineering, embeddings, retrieval, and evaluation.
• Design and optimize vector databases and ensure security and reliability.

Skills

Python

Backend development

LLM

Generative AI

AWS

FastAPI/Flask

Leadership

Code reviews

Tools

LangChain

Pinecone

Chroma

FAISS

Milvus

OpenAI

Anthropic

Hugging Face

Job description

We are seeking a Senior AI Solutions Architect to lead the architecture and development of scalable Generative AI, LLM, and RAG solutions. This is a hands‑on technical leadership role focused on architecture, Python development, AWS, and production AI applications.

Responsibilities

• Own the end-to-end architecture and technical design of LLM and Generative AI solutions.
• Translate business requirements into scalable solution architectures, technical plans, and development tasks.
• Define architecture standards, integration patterns, technical decisions, and engineering best practices.
• Provide technical direction, mentor engineers, and lead design and code reviews.
• Design and develop scalable Python APIs and microservices using FastAPI, Flask, or similar frameworks.
• Architect and implement LLM applications, LangChain workflows, and RAG pipelines.
• Define strategies for prompt engineering, embeddings, chunking, retrieval, re‑ranking, and model evaluation.
• Design and optimize vector database solutions using Pinecone, Chroma, FAISS, Milvus, or similar technologies.
• Establish monitoring and evaluation for quality, relevance, latency, reliability, safety, and cost.
• Design secure, scalable, and resilient AI services on AWS, including Lambda, EC2, S3, EKS, and RDS.
• Partner with DevOps/MLOps teams on CI/CD, infrastructure automation, observability, incident response, and production support.
• Ensure solutions meet enterprise requirements for security, governance, availability, scalability, fault tolerance, and operational readiness.

Required Qualifications

• Extensive software engineering experience with technical leadership responsibilities.
• Strong hands‑on Python and backend development experience.
• Experience with FastAPI, Flask, or comparable frameworks.
• Proven experience delivering production LLM–Generative AI and RAG applications.
• Strong knowledge of LLM architecture, prompt engineering, embeddings, vector databases, retrieval, re‑ranking, and evaluation.
• Experience with OpenAI, Anthropic, Hugging Face, LangChain, or similar platforms/frameworks.
• Strong AWS cloud architecture and deployment experience.
• Experience with microservices, APIs, cloud security, scalability, and distributed systems.
• Strong experience leading architecture/design reviews, code reviews, technical planning, and complex engineering initiatives.
• Ability to mentor engineers and influence technical decisions without formal management authority.

Preferred Skills

• Experience with MLOps, CI/CD, infrastructure as code, and observability.
• Experience with enterprise AI governance, security, and responsible AI practices.
• Experience optimizing AI applications for performance, reliability, and cost.
• Experience working with cross-functional application, data, cloud, security, DevOps, and platform teams.