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.

Key Responsibilities

• Strategic Leadership & Team Management
  • 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
• Technical Execution
  • 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
• Development & Innovation
  • 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
• Collaboration & Governance
  • 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

Here's What You Need

• 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)

Bonus Points If You 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 Core Competencies
• 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

Security Requirements

• Must have an active TS/SCI with polygraph