AI Architect – Agentic & Generative AI

ob Description : As AI Architect – Agentic & Generative AI, you will be responsible for defining, building, and scaling enterprise-grade agentic AI architecture on AWS.

Do you have the right skills and experience for this role Read on to find out, and make your application.

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.