Applied AI Engineer

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

Job summary

Acunor is seeking a hands-on Applied AI Engineer to design, build, and productionize LLM-powered agents and AI workflows on an AWS-native Bedrock platform. This production engineering role focuses on turning business use cases into reliable AI systems, with CI/CD, guardrails, and observability.

You will work with Bedrock capabilities, RAG pipelines, tool calling, and enterprise data sources, integrating with Lambda, Step Functions, SQS/SNS, API Gateway, and CloudWatch for telemetry.

Qualifications

• 8+ years of software engineering experience.
• 2.5+ years building production LLM applications (agents, RAG pipelines).
• Strong Python and/or TypeScript skills.
• Hands-on AWS experience; Bedrock preferred.

Responsibilities

• Design, build, and deploy LLM-powered agents, workflows, and applications using Amazon Bedrock.
• Work with Bedrock capabilities including Bedrock Agents, Knowledge Bases, Guardrails, and multiple foundation models.
• Build agentic workflows incorporating RAG, tool/function calling, APIs, and enterprise data sources.
• Develop using standardized AI platform templates, CI/CD pipelines, guardrails, and evaluation harnesses.
• Build and maintain LLM evaluation suites as part of the engineering lifecycle.

Skills

8+ years

LLM production

Python

TypeScript

API design

Prompt engineering

LLM evaluation

AWS Bedrock

AWS services

Tools

Bedrock

OpenAI API

Anthropic API

AWS

API Gateway

Job description

Work Hours: Must work Pacific Time (PST/PDT) business hours

Employment Type: Long-Term Contract

About the Role

We are seeking a hands-on Applied AI Engineer to design, build, evaluate, and productionize LLM-powered agents and AI workflows.

This is a production engineering role rather than a research-only or proof-of-concept position. You will turn business use cases into reliable AI systems using an AWS-native platform with Amazon Bedrock as the foundation-model layer.

Engineers will work within standardized platform templates, CI/CD pipelines, guardrails, and evaluation frameworks while building AI applications that are reliable, observable, measurable, and ready for production.

Key Responsibilities

• Design, build, and deploy LLM-powered agents, workflows, and applications using Amazon Bedrock.
• Work with Bedrock capabilities including Bedrock Agents, Knowledge Bases, Guardrails, and multiple foundation models.
• Build agentic workflows incorporating RAG, tool/function calling, APIs, and enterprise data sources.
• Develop using standardized AI platform templates, CI/CD pipelines, guardrails, and evaluation harnesses.
• Build and maintain LLM evaluation suites as an integral part of the engineering lifecycle.
• Work with golden datasets, regression testing, and LLM-as-a-judge evaluation approaches.
• Implement prompt and context engineering strategies for reliable production behavior.
• Develop structured outputs, retries, fallbacks, and graceful degradation mechanisms.
• Integrate AI agents with enterprise applications and data through APIs and AWS services such as Lambda, Step Functions, SQS/SNS, and API Gateway.
• Instrument AI applications for quality, latency, token consumption, cost, and operational telemetry.
• Use services such as CloudWatch and Bedrock invocation metrics to monitor production systems.
• Collaborate directly with business users to rapidly iterate, demonstrate solutions, gather feedback, and deliver production functionality.

Required Qualifications

• 8+ years of software engineering experience.
• At least 2.5+ years of experience building production LLM applications, including agents, RAG pipelines, and tool/function calling.
• Strong programming skills in Python and/or TypeScript.
• Strong API engineering experience, including API design, versioning, authentication, and error handling.
• Strong practical experience with prompt engineering and context engineering.
• Hands-on experience developing LLM evaluation approaches including golden datasets, LLM-as-a-judge, and regression suites.
• Hands-on AWS experience.
• Production experience with Amazon Bedrock strongly preferred.
• Candidates with strong production experience using OpenAI/Anthropic APIs combined with AWS may also be considered if they can ramp quickly on Bedrock.
• Experience building reliable, production-grade AI systems rather than only prototypes or research projects.
• Ability to work full Pacific Time (PST/PDT) business hours.

Preferred Qualifications

• Strong information-retrieval/RAG experience, including chunking strategies, embeddings, hybrid search, and re-ranking.
• Experience with OpenSearch, pgvector, or Amazon Bedrock Knowledge Bases.
• Healthcare data experience involving PHI, PII, or HIPAA-aware engineering.
• LLM cost optimization experience, including model routing, prompt caching, batch inference, and throughput optimization.
• Infrastructure-as-Code experience using Terraform or AWS CDK.