Junior DevOps Engineer (GCP)

Role Summary This role is focused on building agentic AI systems and establishing a core AI capability within the organization. The engineer will design, develop, and deploy advanced AI agents and create foundational frameworks for future AI-driven solutions.

Key Responsibilities

• Core Development & Architecture
  Analyze, design, develop, test, and implement complex applications
  Build enterprise-level applications and custom integrations
  Design, code, debug, and document software solutions
  Evaluate system interdependencies and impacts of changes
• AI & Advanced Systems
  Develop and deploy agentic AI systems
  Build frameworks for generative AI use cases
  Research, test, and optimize AI models and agent frameworks
  Monitor and improve AI behavior in production environments
• Technical Leadership (20%)
  Lead integration of applications across business systems
  Design scalable structures and solutions for enterprise software
• Consulting & Collaboration (15%)
  Act as internal consultant and mentor
  Work with stakeholders to define business and technical requirements
  Ensure alignment with IT strategy and architecture standards
• Strategic Design & Innovation (15%)
  Recommend long-term IT and architecture improvements
  Evaluate build vs. buy decisions
  Contribute to data and component architecture design
• System Development & Problem Solving (15%)
  Solve complex business and technical problems
  Develop new approaches, techniques, and data sources
• Standards & Lifecycle Management (15%)
  Define development standards and best practices
  Participate in full SDLC (design deployment support)
  Ensure timely and budget-conscious delivery
• Leadership & Mentorship (15%)
  Guide junior developers and analysts
  Lead or coordinate complex projects
  Resolve cross-team technical issues
• Testing & Documentation (5%)
  Perform testing, debugging, and validation
  Maintain technical documentation

Required Skills & Qualifications

Education Bachelor's degree in Computer Science, IT, or related field OR 4 years relevant experience OR Associate's degree + 2 years relevant experience

Experience 8+ years in application development, systems testing, or related fields 3 6 years in AI/ML or related domains

Technical Skills Core Technologies Python (advanced proficiency) JavaScript / TypeScript API design AI / ML & Agentic Systems Generative AI development (end-to-end) Agentic AI concepts (reasoning, planning, tool use) Prompt engineering, RAG, and AI system design Experience with AI models (e.g., OpenAI, Claude) Frameworks & Tools LangChain, LangGraph, and similar frameworks AI agent development tools and ecosystems Infrastructure & DevOps AWS (preferred) or other cloud platforms CI/CD pipelines Docker & Kubernetes GitHub and modern development workflows Systems Knowledge Multi-platform environments (mainframe, midrange, PC/LAN) Software architecture and system integration Performance monitoring and optimization Nice-to-Have Skills FastAPI or Flask SQL and database experience AutoGen, MCP, embeddings, knowledge stores Reinforcement learning and planning algorithms Multi-agent systems Multi-cloud experience (AWS, Azure, Google Cloud Platform) Model fine-tuning and advanced prompt engineering Soft Skills Strong analytical and problem-solving abilities Effective verbal and written communication Ability to work under pressure in fast-paced environments Team collaboration and leadership skills Attention to detail Strong interpersonal and relationship-building skills Work Environment Fast-paced, project-oriented environment Multi-platform technical ecosystem May require occasional 24/7 responsiveness Strong focus on innovation, collaboration, and customer needs Day-to-Day Activities Hands-on Python development for AI systems Designing and implementing AI architectures Integrating AI agents with backend services Deploying solutions via CI/CD pipelines Researching and testing new AI models/frameworks Collaborating with data scientists and stakeholders Monitoring and improving production AI systems Not a Fit If Experience is limited to traditional ML (e.g., regression/classification) Lack of exposure to Generative AI or agentic systems Team & Culture Innovative, collaborative, and fast-paced Focused on building next-generation enterprise AI solutions Emphasis on creativity, continuous learning, and impact Opportunity to shape long-term AI strategy Requires strong hands-on Python skills and a deep understanding of end-to-end RAG pipeline design. Must explain the full RAG implementation and Python programming proficiency.

For applications and inquiries, contact: hirings@openkyber.com