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GenAI Engineer

Job in Denver, Denver County, Colorado, 80285, USA
Listing for: Magicforce
Full Time position
Listed on 2026-08-01
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), DevOps, Cloud Engineer - Software, Software Architect
Salary/Wage Range or Industry Benchmark: 140000 - 230000 USD Yearly USD 140000.00 230000.00 YEAR
Job Description & How to Apply Below

Seeking an experienced Gen AI Sr. Engineer to design, develop, deploy, and govern scalable Agentic AI solutions using Python, ADK, LLMs, multi-agent systems, GCP, Terraform, and CI/CD
, while establishing architectural standards, AI governance, observability, and enterprise-grade AI application delivery.

Responsibilities –
  • AI Agent Development (40%) Design, develop, and maintain AI agents and AI-powered applications using Python and ADK. Develop reusable agent frameworks, orchestration workflows, and integrations. Build intelligent workflows leveraging LLMs, RAG, tool calling, and multi-agent systems.
  • Ensure reliability, scalability, observability, and performance of AI agents. Cloud Deployment & Operations (25%) Deploy, monitor, and optimize AI applications and agents on Google Cloud Platform. Manage cloud-native services, APIs, compute resources, and AI infrastructure. Implement monitoring, logging, security, and operational best practices. Optimize infrastructure and application performance for cost and efficiency.
  • Collaboration & Integration (15%) Partner with data scientists, analysts, architects, and business stakeholders.
  • Translate business requirements into AI-enabled technical solutions. Integrate AI agents into existing enterprise applications and workflows. Participate in solution design, architecture reviews, and stakeholder discussions.
  • Infrastructure Automation (10%) Develop Infrastructure as Code (IaC) solutions using Terraform. Automate environment provisioning, deployments, and cloud configurations.
  • Implement CI/CD pipelines supporting AI application life cycles. Quality Engineering & Continuous Improvement (5%) Perform unit testing, integration testing, and troubleshooting. Improve agent evaluation, observability, and operational excellence.
  • Resolve production issues and optimize solution performance.
  • Other Duties (5%) Support innovation initiatives and continuous learning. Contribute to AI best practices, standards, and reusable frameworks.
Educational

Qualifications:

-

Engineering Degree - BE/ME/BTech/MTech/BSc/MSc.

Technical certification in multiple technologies is desirable.

Skills:

-

Mandatory skills

  • Programming & Development Python (Expert level) Object-Oriented Programming (OOP) REST API Development Microservices Architecture Git / Git Hub Agentic AI & Generative AI Agent Development Kit (ADK) Agentic AI solutions Multi-Agent Systems
  • Prompt Engineering LLM Integration (Gemini, OpenAI, Claude, etc.) Tool Calling and Function Calling AI Agent Orchestration Frameworks Google Cloud Platform (GCP) Vertex AI Cloud Run Cloud Functions Cloud Storage Pub/Sub Big Query IAM Monitoring & Logging Cloud Build Infrastructure & Dev Ops Terraform CI/CD Pipelines Docker Kubernetes (GKE) Infrastructure as Code (IaC) Testing & Operations Unit Testing Integration
  • Testing Debugging & Troubleshooting Performance Optimization Monitoring & Observability L4 - L7 (Tech Lead
    - Architect
    - Principal)
  • Proven experience architecting and delivering systems using agentic IDEs Ability to:
    Define architectural intent that agents can follow
  • Break features into agent executable tasks
  • Govern AI autonomy (guardrails, permissions, reviews) Integrate agentic workflows into CI/CD pipelines Experience supervising AI agents across:
  • Multi service systems Legacy modernization Large codebases / monorepos Strong understanding of:
    Security implications of autonomous code execution Compliance, auditability, and traceability
  • AI assisted SDLC operating models Core Responsibility:
    Guide effective use of agentic IDEs for complex, multi-module or cross-service changes Establish review practices and quality checks for AI-generated code
  • Mentor team members on balancing autonomy, correctness, and maintainability in AI-assisted development Design system architectures that support AI-augmented and agentic development workflows
  • Define guardrails, standards, and governance for the use of autonomous coding agents Evaluate impact of agentic IDEs on SDLC, CI/CD pipelines, security posture, and technical debt

GenAI, AgenticAI, Python, ADK, VertexAI, Cloud

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