AI/ML Engineer – Amazon Bedrock

Qualifications

• Strong hands-on experience with Amazon Bedrock (mandatory)
• Proven experience building and deploying LLM-based solutions in production environments
• Solid expertise with AWS services, including Lambda, S3, IAM, CloudWatch, and related cloud components
• Strong programming skills in Python (or similar languages commonly used for AI/ML development)
• Experience with prompt engineering, embeddings, vector stores, and RAG architectures
• Ability to translate business problems into scalable, AI-driven solutions and deliver measurable value
• Experience with SageMaker, vector databases, or semantic search
• Prior work on enterprise GenAI use cases (search, summarization, Q&A, insights)
• Exposure to AI governance, security, or responsible AI practices
• 5–7+ years in AI/ML, data engineering, or advanced software engineering
• Has actually built GenAI solutions, not just experimented
• Comfortable working in fast-moving, cross-functional teams
• Strong problem-solving and communication skills

Responsibilities

• These roles will focus on designing, building, and operationalizing GenAI solutions using AWS native services, with a strong emphasis on foundation models, RAG pipelines, and enterprise-grade insight generation
• Build and deploy Generative AI solutions using Amazon Bedrock
• Develop and integrate foundation model workflows, including prompting, fine-tuning, and evaluation
• Design and implement Retrieval-Augmented Generation (RAG) pipelines for domain-specific intelligence
• Generate insights from structured and unstructured data using LLMs and AWS AI services
• Integrate models into backend services and APIs, enabling seamless enterprise workflow automation
• Collaborate closely with product, data, and cloud engineering teams to deliver production-ready GenAI capabilities
• Monitor, optimize, and enhance model performance, reliability, and operational efficiency

Full Description

We are seeking Generative AI Engineers with hands-on experience in Amazon Bedrock to help build advanced AI models and generate actionable insights for enterprise use cases.

These roles will focus on designing, building, and operationalizing GenAI solutions using AWS native services, with a strong emphasis on foundation models, RAG pipelines, and enterprise-grade insight generation.

Key Responsibilities:

• Build and deploy Generative AI solutions using Amazon Bedrock

• Develop and integrate foundation model workflows, including prompting, fine-tuning, and evaluation

• Design and implement Retrieval-Augmented Generation (RAG) pipelines for domain-specific intelligence

• Generate insights from structured and unstructured data using LLMs and AWS AI services

• Integrate models into backend services and APIs, enabling seamless enterprise workflow automation

• Collaborate closely with product, data, and cloud engineering teams to deliver production-ready GenAI capabilities

• Monitor, optimize, and enhance model performance, reliability, and operational efficiency

Required Skills & Experience:

• Strong hands-on experience with Amazon Bedrock (mandatory)

• Proven experience building and deploying LLM-based solutions in production environments

• Solid expertise with AWS services, including Lambda, S3, IAM, CloudWatch, and related cloud components

• Strong programming skills in Python (or similar languages commonly used for AI/ML development)

• Experience with prompt engineering, embeddings, vector stores, and RAG architectures

• Ability to translate business problems into scalable, AI-driven solutions and deliver measurable value.

Nice to Have

• Experience with SageMaker, vector databases, or semantic search

• Prior work on enterprise GenAI use cases (search, summarization, Q&A, insights)

• Exposure to AI governance, security, or responsible AI practices.

Qualifications:

• 5–7+ years in AI/ML, data engineering, or advanced software engineering

• Has actually built GenAI solutions, not just experimented

• Comfortable working in fast-moving, cross-functional teams

• Strong problem-solving and communication skills