AI Solutions Architect at Accenture Federal Services in Columbia, MD

Job description

At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more. Join us to drive positive, lasting change that moves missions and the government forward! 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 t