> Markdown version of [/jobs/ext/3631273-ai-solution-architect](https://www.wearedevelopers.com/jobs/ext/3631273-ai-solution-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# AI Solution Architect

- **Company:** Coforge Limited
- **Location:** River Grove, IL, United States
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Decision Support Systems, Distributed Systems, Python (Programming Language), Performance Tuning, Enterprise Application Integration, QLoRA, Google Cloud, Retrieval-Augmented Generation, Large Language Models, Agentic-AI, CrewAI, AutoGen, Artificial Intelligence Governance, Semantic Kernel, Microservices
- **Published:** October 8, 2026
- **Apply:** https://www.disabledperson.com/jobs/75918385-ai-solution-architect

## About the Role

Skills: Core AI & GenAI, Architecture & Design, LLM?driven workflows, agentic frameworks, API, Cloud Platforms

Experience: 15+ years, * Hands?on experience with agentic frameworks (e.g., LangGraph, AutoGen, CrewAI, Semantic Kernel, custom agent orchestration).

 * Strong understanding of RAG, embeddings, vector databases, and knowledge grounding.
 * Experience with fine?tuning techniques (LoRA / QLoRA) and evaluation strategies.

Architecture & Engineering

 * Strong background in distributed systems, APIs, microservices, and cloud?native architectures.
 * Proficiency in Python and familiarity with enterprise integration patterns.
 * Experience with cloud platforms (Azure, AWS, GCP) and secure enterprise deployments.
 * Knowledge of observability, monitoring, and cost management for AI systems.

## Description

The AI architect will define end?to?end agent frameworks, ensure alignment with available enterprise environment, guardrails, and partner closely with engineering, QE, security, and compliance teams., Business & Stakeholder Leadership

 * Translate business problems into agent?driven solution blueprints.
 * Partner with senior stakeholders to identify high?impact use cases (automation, decision support, quality, operations).
 * Provide executive?level guidance on agentic AI adoption, maturity models, and roadmaps.
 * Support client conversations, RFPs, solution pitches, and thought leadership.

Architecture & Design

 * Define reference architectures for agentic AI systems (single?agent, multi?agent, hierarchical, tool?using agents).
 * Design LLM?driven workflows integrating reasoning, planning, memory, tools, and human?in?the?loop controls.
 * Architect RAG?based and tool?augmented agents using enterprise data sources, APIs, and workflows.
 * Ensure scalability, resilience, observability, and cost optimization of agent platforms.

Governance, Risk & Guardrails

 * Establish AI guardrails covering safety, bias, explainability, auditability, and regulatory compliance.
 * Define agent lifecycle management (design, testing, deployment, monitoring, retirement).
 * Partner with Risk, Legal, Security, and QE teams to ensure model risk management (MRM) and enterprise readiness.
 * Drive standards for agent testing, validation, and certification (functional, non?functional, and ethical).