Description

Key Responsibilities

GenAI Application Development

• Design and build generative AI applications from concept to production deployment
• Translate business requirements into scalable GenAI system architectures
• Develop LLM-powered tools, APIs, internal platforms, and automation workflows
• Implement solutions using RAG, prompt engineering, tool calling, and orchestration frameworks
• Prototype and evaluate emerging GenAI tools for business applicability

Full-Stack Engineering & System Design

• Build and maintain full-stack applications (frontend and backend)
• Design scalable, secure, and maintainable system architectures
• Develop and consume APIs following best practices
• Ensure integration of AI components into enterprise applications

Cloud, DevOps & Production Readiness

• Deploy applications on cloud platforms (AWS, Azure, or GCP)
• Implement CI/CD pipelines, containerization, and deployment automation
• Ensure monitoring, scalability, and reliability of production systems
• Apply DevOps best practices for enterprise-grade delivery

Stakeholder Collaboration & Communication

• Collaborate with engineering and business stakeholders to define solutions
• Communicate technical tradeoffs and architecture decisions clearly
• Independently own end-to-end technical execution of projects
• Stay current with evolving GenAI technologies and industry trends

Required Qualifications

• 3–5+ years of professional experience in software engineering or AI engineering
• Strong proficiency in Python
• Full-stack development experience (frontend + backend)
• Experience building and deploying production software systems
• Strong cloud experience (AWS, Azure, or GCP)
• Experience with CI/CD pipelines, containerization, and DevOps practices
• Strong API design and integration experience
• Proficiency with Git and modern development workflows
• Strong problem-solving and systems thinking skills
• Ability to work independently in large enterprise environments

Preferred Qualifications

• Experience building LLM-powered applications
• Experience with agentic/orchestration frameworks (e.g., LangChain, LangGraph, AutoGen, or similar)
• Exposure to GenAI use cases such as RAG and tool-calling architectures
• Experience in energy, utilities, or industrial domain environments

Key Skills

Education

Any Gradute