Gen AI Solutions Architect

Gen AI Solutions Architect
Location: Dallas (Hybrid)
Total Compensation: Up to $200K


Company Summary
We are a digital engineering firm delivering production-grade AI, data, and platform solutions for enterprise clients in regulated industries. Our teams focus on building systems that ship, scale, and perform under real operational constraints. We value hands-on ownership, technical rigor, and measurable outcomes over theory or advisory work.


Position Summary
We are hiring a hands-on Senior GenAI Solutions Architect to design, build, tune, and deploy production Generative AI systems. This is a delivery-first role. You will personally implement GenAI pipelines, own architectural decisions through code, and be accountable for quality, latency, cost, and reliability in production environments.
This is not a strategy or advisory role. Candidates must have recent experience writing code and shipping GenAI systems used by real users.


What You Will Do

• Personally design, build, and deploy production GenAI applications and agentic systems.
• Own end-to-end GenAI pipelines including data ingestion, embeddings, retrieval, orchestration, evaluation, and monitoring.
• Implement and tune RAG pipelines, including chunking strategies, embeddings selection, hybrid search, reranking, and grounding.
• Build and manage agentic workflows including task planning, tool invocation, memory handling, and failure recovery.
• Tune model parameters, prompts, and retrieval logic to optimize response quality, latency, and cost.
• Define and maintain evaluation frameworks including golden datasets, regression testing, and human-in-the-loop review.
• Diagnose and fix real production issues such as hallucinations, retrieval failures, latency spikes, and cost overruns.
• Implement security, privacy, and governance controls including PII handling, auditability, and prompt-injection defenses.
• Produce clear architecture documentation tied directly to implemented systems.
• Collaborate with product, security, and engineering teams to take systems from PoC to stable production.

What You Bring

• 10+ years of software engineering or solution architecture experience with recent hands-on GenAI delivery.
• Proven experience personally building and shipping multiple production GenAI systems.
• Strong hands-on coding skills in Python or TypeScript.
• Deep experience with RAG architectures and retrieval optimization.
• Experience building and operating agentic AI systems beyond simple chat flows.
• Hands-on experience with vector databases and embedding workflows.
• Practical experience tuning LLM parameters and debugging model behavior.
• Experience implementing evaluation, monitoring, and observability for GenAI systems.
• Experience working in regulated or enterprise environments with strong governance requirements.
• Ability to clearly explain technical tradeoffs and decisions.

Nice to Have

• Model fine-tuning or PEFT experience.
• LangChain, LlamaIndex, or custom orchestration frameworks.
• MLOps or LangOps experience for GenAI systems.
• Experience optimizing token usage and inference cost at scale.

Not a Fit If

• Your experience is primarily AI strategy, advisory, or consulting without direct implementation ownership.
• You have not personally written and maintained GenAI production code.