GenAI Engineer C2C Remote
Remote / Online - Candidates ideally in
Cherry Hill, Camden County, New Jersey, 08034, USA
Listed on 2026-09-24
Cherry Hill, Camden County, New Jersey, 08034, USA
Listing for:
Tech Mirrors
Remote/Work from Home
position Listed on 2026-09-24
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Backend Developer, Python
Job Description & How to Apply Below
GenAI Engineer
Location:
Remote
Employment Type:
Contract
Exp : 15+ years
Job description Required Technical Skills Must Have- Strong backend engineering experience with Python or Type Script.
- Production experience with:
- Agent orchestration
- Tool calling
- Workflow routing
- Multi-agent chaining
- StrongAPI and schema design experience.
- Experience designing structured JSON input/output contracts.
- Experience combining:
- User intent
- Conversation history
- Screen/workflow context
- User filters
- Application state
- into structured agent requests.
- Experience transforming GenAI/agent results into:
- Grounded narratives
- Tables
- Charts
- Citations
- Consistent JSON/application responses
- Hands-on experience building and deploying production GenAI services using:
- AWS
- Amazon Bedrock
- Agent Core
- Strong understanding of production software engineering practices.
- Ability to independently deliver tested, production-ready code with minimal guidance.
- Python
- Type Script
- AWS
- Amazon Bedrock
- Agent Core
- GenAI
- LLMs
- Agent Orchestration
- Multi-Agent Systems
- Tool Calling
- Workflow
- Routing
- Capability Discovery
- Agent Catalogs
- Reusable Skills
- MCP
- API Design
- JSON Schemas
- RAG
- Enterprise AI Applications
- Design and implement enterprise-grade
GenAI orchestration services using Python or Type Script. - Build workflow routing, agent chaining, tool calling, and multi-agent orchestration capabilities.
- Develop reusable agent tools, skills, workflows, and capability definitions.
- Implement capability discovery mechanisms that identify the appropriate agent, tool, or skill for a user request.
- Combine user intent, conversation history, screen context, workflow state, and filters into structured downstream agent requests.
- Design robustAPI contracts and structured JSON schemasfor communication between application services, agents, tools, and data services.
- Integrate existing agents and structured-data query capabilities into a unified GenAI application layer.
- Transform agent responses into grounded narratives, tables, charts, citations, and standardized response payloads.
- Implement validation, error handling, observability, and resilience for production GenAI workflows.
- Build and deploy GenAI services usingAWS, Amazon Bedrock, and Agent Core.
- Develop production-ready code with appropriate unit testing, integration testing, logging, monitoring, and CI/CD.
- Collaborate with architects, product teams, data engineers, and AI engineers to evolve reusable GenAI application patterns.
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