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Senior AI Engineer
Job Description
Senior AI Engineer - Agentic AI, AWS & Automation
Experience: 10 Years
Role Overview
We are looking for a Senior AI Engineer with 10 years of experience to lead the design and
implementation of enterprise AI solutions on AWS. This role will focus on architecting and
building scalable chatbot platforms, advanced RAG systems, agentic AI work flows, multi -
agent solutions, and business process automation.
The ideal candidate should have strong hands -on engineering experience, a solid
understanding of GenAI application architecture, and the ability to move solutions from
proof of concept into secure, maintainable, production -ready systems.
Key Responsibilities
Lead the architecture, design, and development of AI -powered applications on AWS
using Amazon Bedrock and related cloud -native services.
Build and productionize enterprise chatbot platforms with retrieval, citations, tool
use, orchestration, and integrations with internal business systems.
Design advanced RAG pipelines for enterprise data, including ingestion, retrieval,
ranking, grounding, and response quality improvement.
Develop agentic workflows and multi -agent systems for complex, multi -step
business processes.
Design and implement action -based integrations with APIs, Lambda functions,
databases, internal services, and workflow tools.
Establish best practices for prompt design, LLM integration, evaluation,
observability, retries, fallback handling, and deployment patterns.
Lead automation initiatives using AI and non -AI approaches depending on business
fit and operational reliability.
Mentor junior engineers and review designs, implementations, and technical
decisions.
Work with stakeholders to identify high -value AI use cases and convert them into
scalable solutions.
Partner with platform, cloud, and security teams to ensure production readiness,
access control, and operational stability.
Required Qualifications
4 years of experience in software engineering, backend engineering, AI
engineering, machine learning engineering, or related roles.
Strong hands -on experience with AWS services such as Bedrock, Lambda, API
Gateway, S3, DynamoDB, CloudWatch, Step Functions, IAM, and event -
driven/serverless architectures.
Proven experience building production -grade chatbot or GenAI applications.
Strong experience with RAG architecture, embeddings, retrieval strategies, vector
stores, and grounded response generation.
Experience designing agentic workflows, tool -calling systems, or multi -agent
solutions.
Strong programming skills in Python.
Working experience with Node.js and/or TypeScript.
Experience designing robust API integrations and enterprise service interactions.
Strong understanding of system design, reliability, observability, and scalable
backend architecture.
Experience with CI/CD, code quality practices, and cloud deployment workflows.
Preferred Qualifications
Experience with Amazon Bedrock Agents, Knowledge Bases, and action groups.
Experience with LangGraph, LangChain, Semantic Kernel, or comparable
orchestration tools.
Experience With OpenSearch Or Other Vector/search Infrastructure.
Familiarity with authentication, authorization, and enterprise integration patterns.
Experience designing evaluation frameworks for LLM applications.
Experience with guardrails, hallucination reduction, and response quality controls.
Experience leading small teams or owning technical direction for AI products.
Familiarity with workflow automation tools and operational process automation.
What This Role Will Work On
Production -grade enterprise AI assistants
Multi -agent and agentic workflow systems
RAG architecture for internal enterprise knowledge
AI-enabled and rule -based business process automation
AWS -native AI platforms and reusable architecture patterns
Senior AI Engineer
Job Description
Senior AI Engineer - Agentic AI, AWS & Automation
Experience: 10 Years
Role Overview
We are looking for a Senior AI Engineer with 10 years of experience to lead the design and
implementation of enterprise AI solutions on AWS. This role will focus on architecting and
building scalable chatbot platforms, advanced RAG systems, agentic AI work flows, multi -
agent solutions, and business process automation.
The ideal candidate should have strong hands -on engineering experience, a solid
understanding of GenAI application architecture, and the ability to move solutions from
proof of concept into secure, maintainable, production -ready systems.
Key Responsibilities
Lead the architecture, design, and development of AI -powered applications on AWS
using Amazon Bedrock and related cloud -native services.
Build and productionize enterprise chatbot platforms with retrieval, citations, tool
use, orchestration, and integrations with internal business systems.
Design advanced RAG pipelines for enterprise data, including ingestion, retrieval,
ranking, grounding, and response quality improvement.
Develop agentic workflows and multi -agent systems for complex, multi -step
business processes.
Design and implement action -based integrations with APIs, Lambda functions,
databases, internal services, and workflow tools.
Establish best practices for prompt design, LLM integration, evaluation,
observability, retries, fallback handling, and deployment patterns.
Lead automation initiatives using AI and non -AI approaches depending on business
fit and operational reliability.
Mentor junior engineers and review designs, implementations, and technical
decisions.
Work with stakeholders to identify high -value AI use cases and convert them into
scalable solutions.
Partner with platform, cloud, and security teams to ensure production readiness,
access control, and operational stability.
Required Qualifications
4 years of experience in software engineering, backend engineering, AI
engineering, machine learning engineering, or related roles.
Strong hands -on experience with AWS services such as Bedrock, Lambda, API
Gateway, S3, DynamoDB, CloudWatch, Step Functions, IAM, and event -
driven/serverless architectures.
Proven experience building production -grade chatbot or GenAI applications.
Strong experience with RAG architecture, embeddings, retrieval strategies, vector
stores, and grounded response generation.
Experience designing agentic workflows, tool -calling systems, or multi -agent
solutions.
Strong programming skills in Python.
Working experience with Node.js and/or TypeScript.
Experience designing robust API integrations and enterprise service interactions.
Strong understanding of system design, reliability, observability, and scalable
backend architecture.
Experience with CI/CD, code quality practices, and cloud deployment workflows.
Preferred Qualifications
Experience with Amazon Bedrock Agents, Knowledge Bases, and action groups.
Experience with LangGraph, LangChain, Semantic Kernel, or comparable
orchestration tools.
Experience With OpenSearch Or Other Vector/search Infrastructure.
Familiarity with authentication, authorization, and enterprise integration patterns.
Experience designing evaluation frameworks for LLM applications.
Experience with guardrails, hallucination reduction, and response quality controls.
Experience leading small teams or owning technical direction for AI products.
Familiarity with workflow automation tools and operational process automation.
What This Role Will Work On
Production -grade enterprise AI assistants
Multi -agent and agentic workflow systems
RAG architecture for internal enterprise knowledge
AI-enabled and rule -based business process automation
AWS -native AI platforms and reusable architecture patterns