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Protocol Intelligence
Data-driven signals on your job's competitivenessBroad mid-level AI role with full-stack, cloud, and RPA requirements increases candidate competition.
Core AI, cloud, and full-stack skills are transferable, but enterprise RPA and Azure/AWS specifics increase sensitivity.
Explicit 4–6 years and many mandatory cloud, AI, and full-stack tech requirements make filters stringent.
Job Description
Structured overview of role & requirementsAbout This Role
Own end-to-end design and development of scalable, secure AI-embedded enterprise applications across front-end, back-end, cloud services, and automation workflows.
Architect and implement AI solutions including Generative AI, Retrieval-Augmented Generation, AI agents, document intelligence, intelligent automation, and RPA bots with AI enhancements.
Lead production deployment, CI/CD, security, operational support, and collaboration across product, engineering, security, and compliance teams to convert proofs of concept into production-ready solutions.
Minimum Requirements
4-6 years of professional software engineering or AI engineering experience.
Bachelor's or Master's degree in Computer Science, AI, Data Science, Engineering, or related discipline.
Strong experience with full-stack development (React, JavaScript/TypeScript, C#/.NET Core, Python, REST APIs) and AI solution architecture on Azure and/or AWS cloud platforms.
Hands-on skills in Generative AI, LLMs, prompt engineering, RAG, Azure AI services, AWS Bedrock, RPA platforms (e.g., UiPath, Automation Anywhere), and secure API development with OAuth2.0, JWT, RBAC.
Ideal Candidate Profile
Experienced in building and operationalizing enterprise-grade AI applications fully integrated into business workflows rather than standalone prototypes.
Strong in cloud-native AI architecture and delivery on Azure and/or AWS with microservices, containers (Docker, Kubernetes), and Infrastructure as Code.
Skilled in intelligent automation combining AI with RPA bots, able to handle secure, compliance-driven environments and evolving technical priorities.