Solution Architect – Agentic AI

Qualifications

• 12+ years of experience in software engineering and AI/ML system architecture, with at least 5 years in agentic or LLM-driven environments
• Deep programming expertise in Python, TypeScript, and Java
• Strong hands-on experience with agentic AI platforms: LangGraph, LangChain, CrewAI, AgentSpace, etc
• Proven experience integrating and deploying models via AWS Bedrock using providers like OpenAI, Anthropic, Meta, and Mistral
• Expertise in speech AI tools such as OpenAI Realtime API, Amazon Novasonic, or equivalent
• Strong grasp of LLM internals, vector stores, contextual memory, prompt engineering, and RAG strategies
• Extensive experience with cloud-native architectures, CI/CD pipelines, API design, and containerization (Docker)
• Excellent communication, systems thinking, and cross-functional collaboration skills
• Experience architecting multi-agent workflows, task orchestration, and tool augmentation systems
• Familiarity with edge AI deployments or streaming data pipelines for real-time AI use cases
• Contributions to open-source AI tools or research publications in agentic systems, multimodal AI, or applied machine learning
• Certifications in cloud architecture (e.g., AWS Certified Solutions Architect) or additional AI/ML credentials

Responsibilities

• We are seeking a highly skilled and hands-on Solution Architect with 12+ years of experience in Artificial Intelligence (AI) and Machine Learning (ML) to lead the design and architecture of agentic AI systems and multimodal LLM-based solutions
• The ideal candidate is a seasoned AI technologist with a deep understanding of agentic frameworks, large language models (LLMs), real-time speech-to-speech AI, and cloud-native architecture
• You will define scalable technical solutions, guide implementation teams, and play a critical role in bringing advanced autonomous AI applications to life
• Architect and design advanced agentic AI solutions leveraging frameworks like LangGraph, LangChain, CrewAI, and Google AgentSpace
• Provide technical leadership in integrating foundation models (e.g., GPT-4o, Claude, LLaMA, Haiku, Nova) via AWS Bedrock
• Define scalable backend architecture using Python, TypeScript, and Java for production-grade AI systems
• Develop blueprints for real-time conversational interfaces using tools like OpenAI Realtime API and Amazon Novasonic
• Guide prompt engineering, model fine-tuning, vector-based memory systems, and RAG pipelines for contextual reasoning and planning
• Lead cloud architecture design, including DevOps pipelines, Docker-based containerization, and deployment strategies on AWS or equivalent platforms
• Collaborate with project managers, AI researchers, and product stakeholders to align technical decisions with business goals
• Evaluate, prototype, and recommend best-fit tools, APIs, and frameworks across the AI/ML ecosystem
• Monitor and optimize the performance, scalability, and robustness of deployed AI agents and subsystems
• Stay current with trends in AGI, multi-agent systems, and multimodal AI, and incorporate emerging practices into the architectural roadmap

Full Description

Job Title: Solution Architect – Agentic AI Systems (Hands-on AI/ML Expertise Required)

Location: Atlanta, GA (Hybrid – primarily onsite)

Long Term Contract

About the Role:

• We are seeking a highly skilled and hands-on Solution Architect with 12+ years of experience in Artificial Intelligence (AI) and Machine Learning (ML) to lead the design and architecture of agentic AI systems and multimodalLLM-based solutions. This Atlanta-based role involves primarily onsite work, with some flexibility for hybrid arrangements.

• The ideal candidate is a seasoned AI technologist with a deep understanding of agentic frameworks, large language models (LLMs), real-time speech-to-speech AI, and cloud-native architecture. You will define scalable technical solutions, guide implementation teams, and play a critical role in bringing advanced autonomous AI applications to life.

Key Responsibilities:

• Architect and design advanced agentic AI solutions leveraging frameworks like LangGraph, LangChain, CrewAI, and Google AgentSpace.

• Provide technical leadership in integrating foundation models (e.g., GPT-4o, Claude, LLaMA, Haiku, Nova) via AWS Bedrock.

• Define scalable backend architecture using Python, TypeScript, and Java for production-grade AI systems.

• Develop blueprints for real-time conversational interfaces using tools like OpenAI Realtime API and Amazon Novasonic.

• Guide prompt engineering, model fine-tuning, vector-based memory systems, and RAG pipelines for contextual reasoning and planning.

• Lead cloud architecture design, including DevOps pipelines, Docker-based containerization, and deployment strategies on AWS or equivalent platforms.

• Collaborate with project managers, AI researchers, and product stakeholders to align technical decisions with business goals.

• Evaluate, prototype, and recommend best-fit tools, APIs, and frameworks across the AI/ML ecosystem.

• Monitor and optimize the performance, scalability, and robustness of deployed AI agents and subsystems.

• Stay current with trends in AGI, multi-agent systems, and multimodal AI, and incorporate emerging practices into the architectural roadmap.

Required Skills & Qualifications:

• 12+ years of experience in software engineering and AI/ML system architecture, with at least 5 years in agentic or LLM-driven environments.

• Deep programming expertise in Python, TypeScript, and Java.

• Strong hands-on experience with agentic AI platforms: LangGraph, LangChain, CrewAI, AgentSpace, etc.

• Proven experience integrating and deploying models via AWS Bedrock using providers like OpenAI, Anthropic, Meta, and Mistral.

• Expertise in speech AI tools such as OpenAI Realtime API, Amazon Novasonic, or equivalent.

• Strong grasp of LLM internals, vector stores, contextual memory, prompt engineering, and RAG strategies.

• Extensive experience with cloud-native architectures, CI/CD pipelines, API design, and containerization (Docker).

• Excellent communication, systems thinking, and cross-functional collaboration skills.

Nice to Have:

• Experience architecting multi-agent workflows, task orchestration, and tool augmentation systems.

• Familiarity with edge AI deployments or streaming data pipelines for real-time AI use cases.

• Contributions to open-source AI tools or research publications in agentic systems, multimodal AI, or applied machine learning.

• Certifications in cloud architecture (e.g., AWS Certified Solutions Architect) or additional AI/ML credentials.