AI Architect Agentic & Generative AI

Job Description

Job Description

Benefits:

• Oppurtunity for Advancement
• Long Term
• Competitive salary

AI Architect Agentic & Generative AI
Work Type: Full-Time, Onsite
Location: Dallas, Texas
Interview Mode: In-Person
Work Auth : Must be authorized to work in the U.S.
Domain: Enterprise AI / Agentic AI / AWS Bedrock
Compensation: Competitive, commensurate with experience

As AI Architect Agentic & Generative AI, you will be responsible for defining, building, and scaling enterprise-grade agentic AI architecture on AWS. This role focuses on establishing frameworks, patterns, and guardrails that enable safe, reliable, and cost-efficient AI solutions, leveraging Amazon Bedrock (Agents, Knowledge Bases, Guardrails, Flows) and Claude models.
You will collaborate with cross-functional teams in product, engineering, data, and security to deliver next-generation AI capabilities including retrieval-augmented generation (RAG), multi-agent orchestration, and governed AI operations driving measurable business impact through intelligent automation and decision-making systems.

Responsibilities

• Define and evolve the enterprise agentic AI architecture, establishing reusable frameworks and standards for RAG, tool/function calling, and multi-agent orchestration.
• Design and implement AI solutions using Amazon Bedrock and integrate with core AWS services (Lambda, Step Functions, EventBridge, ECS/EKS, S3, Aurora, OpenSearch, DynamoDB).
• Drive adoption of agentic AI patterns planning, memory, and human-in-the-loop ensuring alignment with enterprise security and compliance frameworks.
• Guide model selection and optimization (Claude family and Bedrock models), including prompt schema design, adapters, and fine-tuning strategies.
• Implement advanced RAG pipelines with optimized chunking, reranking, grounding, and hybrid/vector retrieval using OpenSearch and pgvector.
• Apply Guardrails and data-governance controls (IAM/ABAC, KMS, private networking) to ensure privacy, PII protection, and compliant operations.
• Establish observability and reliability frameworks including evaluation pipelines, tracing, cost metrics, fallbacks, and A/B testing.
• Collaborate with platform and DevOps teams to enable governed AWS landing zones, CI/CD automation, and environment management for AI workloads.
• Publish architecture blueprints, starter kits, and best-practice guides for AI engineers and developers.
• Mentor engineering teams and contribute to hiring, training, and AI community enablement initiatives.
• Research and assess emerging AWS and open-source agentic tools, proposing pragmatic adoption strategies.

Required Skills & Experience

• 8+ years designing and implementing large-scale distributed or cloud systems (including 4+ years on AWS).
• 2+ years building AI/ML or generative AI solutions in production environments.
• Hands-on experience with Amazon Bedrock (Agents, Knowledge Bases, Guardrails) and Claude models.
• Deep understanding of RAG design, hybrid/vector search (OpenSearch, pgvector), grounding, and citation techniques.
• Proficiency in Python (preferred) or similar modern programming languages.
• Solid grasp of AWS orchestration services (Lambda, Step Functions, EventBridge) and CI/CD practices.
• Applied knowledge of AI governance, security, and observability (IAM, KMS, Guardrails, evaluation, tracing).
• Excellent communication and architectural documentation skills.

Preferred Qualifications

• Expertise in Agentic AI systems, including multi-agent workflows, tool/function calling, and memory architectures.
• Experience with LangChain, LangGraph, or similar orchestration frameworks.
• Advanced prompt design, RAG optimization, and model customization experience.
• AWS Certifications Solutions Architect (Professional) or Machine Learning Specialty.