Note: The job is a remote job and is open to candidates in USA. Acunor is seeking an Applied AI Engineer to design, build, evaluate, and productionize LLM-powered agents and AI workflows on an AWS-native platform using Amazon Bedrock. The role focuses on developing reliable, observable, measurable, and production-ready AI applications, integrating them with enterprise systems, and collaborating with business users to iterate and deliver solutions.
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
Skills
- • 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
- • 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
- • Container experience with ECS/EKS
Benefits
- Remote – United States
- Long-Term Contract
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