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# Full Stack LLM Development Senior Manager

- **Company:** Accenture
- **Location:** United States
- **Experience:** Expert
- **Salary:** $139,300.0 - $269,000.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), A/B Testing, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Code Review, Continuous Delivery, Continuous Integration, Python (Programming Language), Scrum Methodology, OpenAI, Tensorflow, Next.js, Search Technologies, Software Engineering, TypeScript, Web Application Frameworks, Pinecone, Google Cloud, Pytorch, LangChain, ReactJS, Large Language Models, Prompt Engineering, Llamaindex, Generative AI, Fastapi, Web Filtering, Containerization, Kubernetes, Information Technology, HuggingFace, Transformer Architectures, Weaviate, Machine Learning Operations, Front End Software Development, Invoking Functions, Software Version Control, Docker, ChromaDB
- **Published:** October 10, 2026
- **Apply:** https://www.dice.com/job-detail/a90bbee8-b1c0-41a7-b715-a061cda38ebb

## About the Role

* 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, Google Cloud Platform) 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

## Description

* 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