Posted 10 days ago
Applied AI Engineer (Contract)
@ Upstream Works Software
Remote in Canada
Overview
Upstream Works Software is hiring a contract Applied AI Engineer to set up an agentic AI evaluation and demo environment on Amazon Bedrock AgentCore. The work covers AgentCore setup, a golden dataset and evaluation process, and an end-to-end demo built around a business use case. Availability for regular meetings during Eastern Time business hours is required.
Responsibilities:
- Set up Amazon Bedrock AgentCore in AWS environment
- Build and version a golden dataset and evaluation process
- Build and present an end-to-end AgentCore demo
Requirements summary:
- 3+ years hands-on software or AI engineering experience
- Hands-on Amazon Bedrock and AgentCore experience
- Strong Python skills
- Experience designing evaluations for non-deterministic AI systems
Tools & skills
Source and dates
Source type not verified · humi
- Employer posting date
- 2026-10-27
- First seen by our source
- 2026-10-27
- Source record updated
- 2026-10-27
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Mid level |
| Department | Software development |
| Experience | 3+ years |
| Travel | air: none · ground: none |
| Work setting | Office, Home |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Upstream Works Software
| Field | Value |
|---|---|
| Open jobs on Jobsy | 1 |
Applied AI Engineer (Contract)
About the role
Upstream Works Software is hiring a contract Applied AI Engineer to contribute to the setup of our agentic AI evaluation and demo environment on Amazon Bedrock AgentCore.
Upstream Works is a Canadian software company with 25 years of experience in enterprise contact centre software, trusted by Cisco, Amazon Web Services and global partners.
Our platform brings AI into the contact centre, and this engagement will help us prove agent quality before it reaches customers.
You will own the hands on build: setting up AgentCore, creating a golden dataset and evaluation process, and delivering an end to end demo shaped around a real business use case. You will work closely with our Product Lead, who will define the business requirements the demo needs to meet.
Key responsibilities
The work runs in three phases, each with a clear deliverable.
Setup AWS AgentCore
- Lead the setup of Amazon Bedrock AgentCore in our AWS environment, including Runtime, Observability and Evaluations.
- Configure secure access, permissions and logging following AWS best practices.
- Document the setup so our team can maintain and extend it.
Build the golden dataset and evaluation process
- Work with our Product Lead and subject matter experts to define realistic scenarios, expected responses and the steps the agent should take.
- Build and version a golden dataset that reflects real contact centre interactions, using anonymized or synthetic data.
- Design the evaluation approach, including success criteria, built in and custom evaluators, and a repeatable process for regression testing as the agent changes.
- Report on agent quality in a way business stakeholders can understand.
Build an end to end demo in AgentCore
- Build a working agent and connect it to the tools and data the use case needs.
- Shape the demo around the business requirements defined with our Product Lead, and iterate based on feedback.
- Prepare and present the demo to internal stakeholders.
Throughout the engagement, you will share regular progress updates, flag risks early, and leave behind clear documentation and reusable components.
Required Qualifications
- 3 or more years of hands on software or AI engineering experience, including building at least one LLM based application or agent that reached production or real users
- Hands on experience with Amazon Bedrock and Amazon Bedrock AgentCore
- Strong Python skills, including APIs, SDKs and data handling
- Experience building AI agents with tool or function calling, retrieval, and at least one agent framework (for example, Strands, LangGraph, CrewAI or similar)
- Experience designing evaluations for non deterministic AI systems, such as golden datasets, success criteria, LLM as a judge, and regression testing
- Working knowledge of core AWS services, including IAM, CloudWatch, Lambda and S3
- Ability to turn business requirements into a working technical solution with limited direction
- Excellent written and verbal English, and the ability to explain technical results to non-technical stakeholders
- Availability for regular meetings during Eastern Time business hours
Would Be An Asset
- Experience with conversational AI or voice agents (for example, Amazon Connect, Cisco or Genesys)
- AWS certifications, such as AWS Certified AI Practitioner, Machine Learning Engineer Associate or Solutions Architect Associate
- Experience with Model Context Protocol (MCP) or AgentCore Gateway
- Experience setting up evaluation in CI/CD pipelines
- Experience handling sensitive customer data, including anonymization and privacy requirements
Journal
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