Generative AI Engineer

Harnham; United States; On-site; USD 150,000 - 230,000; Full time

Job summary

Harnham seeks an AI Engineer to lead end-to-end AI/ML architecture, development, and deployment for enterprise solutions in a AWS cloud environment. You will own complex systems, influence technical direction, and build production-grade AI applications focused on reliability, scalability, and security.

The role requires hands-on experience with agentic AI, LLM orchestration, and RAG architectures, along with deep AWS exposure including Bedrock, Sagemaker, Lambda, and DynamoDB.

Qualifications

• 5+ years of software engineering delivering production AI/ML or GenAI solutions.
• Hands-on experience with Agentic AI, LLM orchestration, tool calling, and RAG architectures.
• Deep experience with AWS, especially Bedrock, Lambda, DynamoDB, S3, EventBridge, SQS, and Step Functions.
• Strong Python and Node.js programming, including API development.
• Experience with LLM observability, evaluation frameworks, and reliability patterns.
• Experience with Docker and modern cloud deployment.
• Bachelor's degree in CS, engineering, or related field (or equivalent).

Responsibilities

• Design and build agentic AI systems with reasoning workflows and function calling.
• Develop and maintain RAG solutions using embeddings, vector search, and knowledge management.
• Architect and integrate AI apps using AWS Bedrock, Sagemaker, Lambda, and more.
• Establish observability and evaluation frameworks for LLM-based systems.
• Build backend services and APIs in Python and Node.js for cloud-native apps.
• Lead design discussions, mentor engineers, and provide architectural guidance.
• Ensure production reliability with fault tolerance and monitoring.

Skills

Agentic AI

LLM orchestration

AWS Bedrock

Python

Node.js

Docker

Observability

Mentoring

Education

Bachelor's degree in CS or related field

Tools

Bedrock

Sagemaker

Lambda

DynamoDB

S3

EventBridge

SQS

Step Functions

API Gateway

Job description

An innovative technology consultancy seeks an AI Engineer to lead the architecture, development, and deployment of enterprise-scale AI/ML solutions. This position is ideal for a senior-level engineer who enjoys owning complex systems end-to-end, influencing technical direction, and building production-grade AI applications that prioritise reliability, scalability, and security in an AWS Cloud Environment.

Responsibilities

• Design and build Agentic AI systems including reasoning workflows, tool/function calling, and single-agent or multi-agent architectures.
• Develop and maintain Retrieval-Augmented Generation (RAG) solutions using embeddings, vector search, re-ranking, and knowledge management strategies.
• Architect and integrate AI applications using AWS services including Bedrock, Sagemaker, Lambda, DynamoDB, SQS, Step Functions, EventBridge, and API Gateway.
• Establish observability, evaluation frameworks, and monitoring for LLM-based systems using tools such as LangFuse, LangSmith, and RAG evaluation methodologies.
• Build backend services and APIs using Python and Node.js while supporting cloud-native and serverless architectures.
• Lead technical design discussions, mentor engineers, and provide architectural guidance across AI initiatives.
• Ensure production reliability through fault tolerance, fallback mechanisms, monitoring, and operational best practices.

Must Have Qualifications

• 5+ years of software engineering experience with demonstrated success delivering production AI/ML or GenAI solutions.
• Strong hands-on experience with Agentic AI, LLM orchestration, tool calling, function calling, and RAG architectures.
• Deep experience with AWS cloud services, particularly Bedrock, Lambda, DynamoDB, S3, EventBridge, SQS, and Step Functions.
• Strong programming skills in Python and Node.js, including API development and cloud-native applications.
• Experience implementing LLM observability, evaluation frameworks, prompt engineering, and production reliability patterns.
• Experience with Docker and modern cloud deployment methodologies.
• Bachelor's degree in Computer Science, Engineering, or a related technical discipline (or equivalent experience).