job summary:
Senior AI Developer
We're looking for a Senior AI Agent Developer to lead the design, build, and support of enterprise conversational AI agents and the web experiences around them. You'll own key parts of the architecture on Google Cloud Platform (GECX / Dialogflow CX), connect agents to Azure, Google Cloud and ServiceNow, and set the standards for how agents, fulfillment services, and front-end interfaces are built, tested, and released. You'll also mentor engineers and work closely with product, platform, and operations teams.
Key Responsibilities
Agent Architecture and Development
Lead the design of conversational flows, route groups, intents, and LLM-powered tools in GECX / Dialogflow CX, and set patterns for agents built with Google's Agent Development Kit (ADK).
Make architecture decisions for agent orchestration, tool design, and handoffs between agents, fulfillment services, and human agents.
Lead the design of Contact Center AI (CCAI) solutions, including integration with IVR platforms such as Genesys and Amazon Connect.
Define prompt engineering and intent classification standards and evaluate changes against measurable quality criteria.
Backend and Integration
Design and build REST APIs, webhooks, and services in Python (primary) with .NET or Node.js that connect agents to ServiceNow, Azure systems, and IVR platforms.
Establish API contracts, versioning, and error-handling standards, including MCP integration patterns.
Write and optimize SQL for agent lookups, reporting, and conversational analytics.
Front End
Lead the development of responsive, accessible interfaces using HTML, CSS, and TypeScript with React or Angular.
Set front-end patterns for API connection, loading states, error handling, and session management in the browser.
Own security practices for browser-facing code, including CORS, XSS prevention, and secure handling of tokens and secrets.
Build internal dashboards for agent analytics, test results, and admin tasks.
Delivery, Quality, and Operations
Own and improve Azure DevOps pipelines that validate and deploy agent configurations, fulfillment services, and front-end builds. Review and approve changes to YAML pipelines.
Define infrastructure as code standards with Terraform for the agent platform, fulfillment services, and supporting cloud resources, and review changes to Terraform modules.
Define the testing strategy across unit tests, webhook API tests, dialog flow regression tests, and front-end component tests. Drive coverage targets and quality gates.
Lead incident investigation and root-cause analysis for production issues and failed test runs. Document findings and drive follow-through.
Monitor agent performance and reliability and contribute to observability and AIOps practices.
Leadership and Collaboration
Mentor junior and mid-level developers through code reviews, pairing, and technical guidance.
Participate in and help lead sprint planning, backlog refinement, and Program Increment (PI) planning within a SAFe environment.
Partner with product owners and stakeholders to translate business requirements into technical designs and realistic delivery plans.
Keep architecture diagrams, flow designs, API documentation, and runbooks current, and set documentation standards for the team.
Required Qualifications
Bachelor's degree in computer science, IT, or a related field, or equivalent practical experience
8+ years of software engineering experience, including at least 1 years building production conversational AI or LLM-based applications
Advanced proficiency in Python, with working proficiency in .NET and JavaScript or TypeScript
Strong experience with REST APIs, JSON, webhooks, MCP, and calling APIs from browser applications
Hands-on experience with Dialogflow CX or GECX, or comparable conversational AI platforms
Hands-on experience with Contact Center AI (CCAI) solutions or experience with IVR platforms such as Genesys or Amazon Connect
Strong SQL skills.
Experience designing and maintaining automated test suites using frameworks such as PyTest, Jest, or xUnit
Experience with Git, CI/CD pipelines, and code review practices
Experience with containers and infrastructure as code (Docker, Kubernetes, or Terraform)
Excellent written and verbal communication, including the ability to explain technical trade-offs to non-technical stakeholders.
Preferred Qualifications
Experience building agents with Google's Agent Development Kit (ADK) or similar agent frameworks
Experience designing prompt strategies, evaluation methods, or intent classification for LLM-based systems
Experience leading front-end testing with Playwright, Cypress, or Selenium
Experience with Azure DevOps pipelines or another enterprise CI/CD tool
Experience with ServiceNow (REST APIs, Flow Designer) or .NET (C#)
Working knowledge of OAuth2, API keys, secrets management, and browser security
Experience with SAFe or other scaled Agile frameworks
Experience with containers (Docker, Kubernetes)
Experience with serverless platforms (Cloud Run, Azure Functions)
Interest in or experience with SRE, observability, and AIOps
Tooling and Environment
Conversational AI and Cloud: Google Cloud Platform (GECX / Dialogflow CX), Microsoft Azure
Contact Center: Contact Center AI (CCAI), Genesys, Amazon Connect
Infrastructure as Code: Terraform
Back end: Python 3.x (primary), .NET (C#), Node.js, SQL
Front end: HTML, CSS, TypeScript / JavaScript, React or Angular
DevOps and Testing: Azure DevOps (Pipelines, Repos), Git, API, unit, and UI testing frameworks
Enterprise Platforms: ServiceNow (REST APIs, Flow Designer)
Agile: SAFe, Jira / Azure Boards
IDEs: Visual Studio Code, Antigravity
location: New York, New York
job type: Contract
salary: $65 - 75 per hour
work hours: 9am to 6pm
education: Bachelors
responsibilities:
Senior AI Developer
We're looking for a Senior AI Agent Developer to lead the design, build, and support of enterprise conversational AI agents and the web experiences around them. You'll own key parts of the architecture on Google Cloud Platform (GECX / Dialogflow CX), connect agents to Azure, Google Cloud and ServiceNow, and set the standards for how agents, fulfillment services, and front-end interfaces are built, tested, and released. You'll also mentor engineers and work closely with product, platform, and operations teams.
Key Responsibilities
Agent Architecture and Development
- Lead the design of conversational flows, route groups, intents, and LLM-powered tools in GECX / Dialogflow CX, and set patterns for agents built with Google's Agent Development Kit (ADK).
- Make architecture decisions for agent orchestration, tool design, and handoffs between agents, fulfillment services, and human agents.
- Lead the design of Contact Center AI (CCAI) solutions, including integration with IVR platforms such as Genesys and Amazon Connect.
- Define prompt engineering and intent classification standards and evaluate changes against measurable quality criteria.
Backend and Integration
- Design and build REST APIs, webhooks, and services in Python (primary) with .NET or Node.js that connect agents to ServiceNow, Azure systems, and IVR platforms.
- Establish API contracts, versioning, and error-handling standards, including MCP integration patterns.
- Write and optimize SQL for agent lookups, reporting, and conversational analytics.
Front End
- Lead the development of responsive, accessible interfaces using HTML, CSS, and TypeScript with React or Angular.
- Set front-end patterns for API connection, loading states, error handling, and session management in the browser.
- Own security practices for browser-facing code, including CORS, XSS prevention, and secure handling of tokens and secrets.
- Build internal dashboards for agent analytics, test results, and admin tasks.
Delivery, Quality, and Operations
- Own and improve Azure DevOps pipelines that validate and deploy agent configurations, fulfillment services, and front-end builds. Review and approve changes to YAML pipelines.
- Define infrastructure as code standards with Terraform for the agent platform, fulfillment services, and supporting cloud resources, and review changes to Terraform modules.
- Define the testing strategy across unit tests, webhook API tests, dialog flow regression tests, and front-end component tests. Drive coverage targets and quality gates.
- Lead incident investigation and root-cause analysis for production issues and failed test runs. Document findings and drive follow-through.
- Monitor agent performance and reliability and contribute to observability and AI
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