AI Solutions Architect

The Full Stack LLM Development Senior Manager leads the design, development, and deployment of enterprise-grade large language model applications. This strategic leadership role bridges technical innovation and business outcomes, overseeing cross-functional teams building end-to-end AI solutions from model fine-tuning to production-scale deployment.

Responsibilities

Lead and mentor a team of 3 ML engineers and full-stack developers; Define technical roadmaps for LLM application development aligned with business objectives; Facilitate sprint planning, code reviews, and architecture design sessions; Manage resource allocation, project timelines, and stakeholder communications; Architect full-stack LLM solutions including frontend interfaces, API layers, vector databases, and model orchestration; Oversee engineering strategies, retrieval-augmented generation (RAG) implementations, and fine-tuning initiatives; Design scalable microservices architectures integrating LLM APIs (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI); Implement MLOps pipelines for model versioning, A/B testing, monitoring, and continuous deployment; Optimize inference performance, cost management, and latency reduction strategies; Build production applications using Python, TypeScript/JavaScript, and modern frameworks (React, Next.js, FastAPI); Develop evaluation frameworks for model performance, safety, and alignment; Implement guardrails, content filtering, and responsible AI practices; Prototype emerging capabilities including function calling, agents, and multi-modal applications; Partner with product managers, external stakeholders, and security teams on requirements and compliance; Present technical proposals and demos to executive leadership; Establish coding standards, documentation practices, and knowledge-sharing initiatives; Manage vendor relationships and evaluate emerging LLM technologies

Requirements

8 years in software engineering or data science with 3 years in leadership roles; 3 years hands-on experience with LLMs and/or generative AI applications; Experience deploying production AI/ML systems at scale; Experience managing cross-functional technical teams; Proficiency with ML frameworks (e.g.: PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex); Experience with vector databases (e.g.: Pinecone, Weaviate, ChromaDB), embeddings, and/or semantic search; Experience with cloud platforms (e.g.: AWS, Azure, GCP) and containerization (e.g.: Docker, Kubernetes); Familiarity with CI/CD, infrastructure-as-code, and/or MLOps tools (MLflow, Weights & Biases); Must have an active TS/SCI with polygraph; Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States

Nice to have

Bachelor's degree in Computer Science, Engineering, or related field (required); Master's degree or PhD in Computer Science, AI/ML, or related discipline (strongly preferred); DoD 8140 Policy Framework; Relevant certifications in prompt engineering, LLM development, or AI ethics; Deep knowledge of LLM architectures, transformer models, and prompt engineering techniques; Strategic thinking with ability to translate business needs into technical solutions; Strong communication skills for technical and non-technical audiences; Experience with Agile/Scrum methodologies and project management; Understanding of data privacy, security, and AI governance frameworks; Passion for staying current with rapidly evolving AI/ML landscape