AI Engineer - AWS Bedrock and AI Services

Read in full - don't ‘just apply’.

Overview

We’re looking for an AI Engineer with expertise in AWS Bedrock, retrieval-augmented generation (RAG) pipelines, and Python who can ship customer-facing features at scale. If you know your way around AWS, vector databases, and prompt engineering, and you love solving real-world AI challenges, we want to hear from you. Bonus points if you’ve fine-tuned models, built B2B SaaS tools, or optimized AI costs.

P.S. Research shows that in order to apply for a job, women feel they need to meet 100% of the criteria while men usually apply after meeting 60%. Regardless of how you identify, if you believe you can do the job and are a good match, we encourage you to apply.

What you'll do

• Implement AI features using AWS Bedrock, focusing on RAG systems, Q&A functionality, and deal coaching tools
• Optimize prompts and AI workflows to improve accuracy, speed, and cost-effectiveness
• Build integrations with AWS AI services (Comprehend, Textract, Transcribe) as needed for our roadmap
• Collaborate closely with full-stack engineers to seamlessly integrate AI capabilities into our platform
• Monitor and improve AI system performance, identifying bottlenecks and optimization opportunities
• Establish best practices for prompt engineering, testing, and AI feature deployment
• Handle AI-specific debugging and troubleshooting for production systems
• Stay current with AWS Bedrock updates and new AI service capabilities

Qualifications

• 3-5 years of software engineering experience with AI/ML implementations
• Hands-on experience with AWS Bedrock or similar AI service platforms (OpenAI API, Azure AI, etc.)
• Strong Python skills and experience with APIs and cloud services
• RAG system experience - building, optimizing, or maintaining retrieval-augmented generation pipelines
• Prompt engineering skills with demonstrated ability to optimize for specific outputs
• Production experience with AI features in customer-facing applications
• AWS fundamentals - comfortable with Lambda, S3, API Gateway, and basic cloud architecture
• Collaborative mindset - able to work effectively with full-stack engineers and product teams
• Experience with vector databases

Nice to have

• AWS certifications (any level)
• Experience with vector databases
• Fine-tuning experience with foundation models
• Background in B2B SaaS or sales tools
• Experience with audio/transcript processing
• Understanding of AI cost optimization strategies

Other Info // How to Apply

How to apply: Submit your CV and a brief note on your relevant experience with AWS Bedrock, RAG pipelines, and AI features. Hiring process: CV screening > Initial Interview > Technical Screening/Live Coding > C8/Culture Fit Interview