Cloud Solutions Architect

Quick Facts

• Role: Architect and build production-grade agentic AI systems leveraging generative AI and LLMs

• Focus: RAG, agent orchestration, evaluation pipelines, and human-in-the-loop safety

• Platform: Deploy on AWS (or equivalent cloud) with secure, scalable operations

Description

As an experienced engineer, you will design, develop, and deliver mission-critical agentic AI applications that prove real-world value using generative AI, LLMs, and autonomous workflows. You will architect modular, reusable AI patterns, integrate multiple model providers (cloud-hosted, local, hybrid), and build solutions optimized for latency, cost, observability, and safety. You will prototype and iterate using evaluation-driven development and continuous experimentation.

Responsibilities

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

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

• Build RAG/memory data pipelines (ingestion, cleaning, chunking, embeddings, indexing, continuous refresh)

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

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

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

• Lead prototyping workshops and collaborate with clients to define solution requirements

• Present solutions to technical and non-technical stakeholders and guide responsible AI practices, ethics, and compliance

Requirements

• 2+ years of software engineering experience

• 2+ years of experience in an AI or ML-focused role in a professional environment

• Experience using an object-oriented language such as Python for 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 patterns

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

• TS/SCI clearance

• Bachelor’s degree

Benefits

• Health, life, disability, financial, and retirement benefits

• Paid leave, professional development, tuition assistance, work-life programs, and dependent care

• Recognition awards program

• Eligibility for benefits depends on working hours and contract requirements