Cloud Solutions Architect

Quick Facts

• Role: Cloud Solutions Architect (Agentic AI / GenAI)

• Focus: Architect production-grade agentic AI systems using LLMs, RAG, evaluation, and safety

Description

Design and deliver production-grade agentic AI systems that demonstrate practical value of generative AI, large language models, and autonomous workflows. Architect modular, reusable AI application patterns and integrate model providers (cloud, local, or hybrid) using structured prompting, tool use, workflow orchestration, and multi-modal reasoning. Deploy secure, scalable solutions on AWS (or equivalent) and iterate quickly using evaluation-driven development.

Responsibilities

• Design adaptable AI architectures supporting multiple model providers, modalities, tool ecosystems, and deployment modes

• Integrate LLMs, embeddings, RAG pipelines, structured outputs, and long-context/memory mechanisms into production-ready systems

• Build data pipelines for ingestion, cleaning, chunking, embedding, indexing, and continuous refresh for RAG and memory

• Implement guardrails, safety filters, access controls, and monitoring for responsible and secure agentic AI deployment

• Deploy AI services securely and at scale on AWS (or equivalent cloud)

• Apply CI/CD and evaluation-driven development (automated testing of prompts/workflows, versioning of prompts/agents, safe model rollouts)

• Use AI assistance tools to accelerate development and debugging while maintaining engineering rigor and code quality

• Collaborate with clients on high-value AI opportunities and solution requirements

• Present solutions to technical and non-technical stakeholders; lead workshops and prototyping sessions

• Provide guidance on responsible AI practices, ethics, and compliance

Requirements

• 2+ years of software engineering experience

• 2+ years of AI/ML-focused professional experience

• Object-oriented programming experience (e.g., Python) applied to AI/ML solution development

• Experience designing and implementing production-grade generative or agentic AI applications

• Experience with RAG architectures, evaluation methodologies, experimentation workflows, and asynchronous/event-driven programming

• Knowledge of data processing for AI, including text, audio, and multi-modal data

• TS/SCI clearance

• Bachelor’s degree

Benefits

• Health, life, disability, financial, and retirement benefits; paid leave

• Professional development and tuition assistance

• Work-life programs and dependent care support

• Recognition awards program

• Work model flexibility: remote/hybrid/onsite expectations may apply; in-person work may be required