GenAI Engineer C2C requirements Remote

GenAI Engineer

Location:Remote

Employment Type:Contract

Exp : 15+ years

Job description

Required Technical Skills

Must Have

• Strong backend engineering experience withPython or TypeScript.
• Production experience with:
• Agent orchestration
• Tool calling
• Workflow routing
• Multi-agent chaining
• StrongAPI and schema designexperience.
• Experience designingstructured 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
• AgentCore
• Strong understanding of production software engineering practices.
• Ability to independently delivertested, production-ready code with minimal guidance.

Key Technologies

• Python
• TypeScript
• AWS
• Amazon Bedrock
• AgentCore
• 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

Key Responsibilities

• Design and implement enterprise-gradeGenAI orchestration servicesusing Python or TypeScript.
• Buildworkflow routing, agent chaining, tool calling, and multi-agent orchestrationcapabilities.
• Develop reusableagent tools, skills, workflows, and capability definitions.
• Implement capability discovery mechanisms that identify the appropriate agent, tool, or skill for a user request.
• Combineuser intent, conversation history, screen context, workflow state, and filtersinto 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 intogrounded 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 AgentCore.
• Develop production-ready code with appropriateunit testing, integration testing, logging, monitoring, and CI/CD.
• Collaborate with architects, product teams, data engineers, and AI engineers to evolve reusable GenAI application patterns.