AI SW Engineer

As an AI Software Engineer, you will be responsible for the end-to-end development, deployment, and support of enterprise-grade AI and software solutions. This includes evaluating and selecting technologies, designing scalable architectures, developing applications, managing infrastructure, implementing CI/CD pipelines, overseeing deployments, and providing ongoing production support. Additionally, you will build, maintain, and optimize the technical platforms and engineering practices that enable teams to efficiently collaborate, develop, deploy, and operate these solutions at scale.

Your responsibilities

• Evaluate business requirements and select appropriate technology stacks, application frameworks, databases, and deployment architectures for AI and non-AI solutions.
• Design, develop, and maintain AI-powered and web applications using Python, Django/Flask, FastAPI, React, REST APIs, LLMs, RAG, and agentic AI frameworks such as LangChain/LangGraph.
• Provision and manage application infrastructure across OpenStack and Azure, including VMs, application hosting, Nginx, HTTPS/TLS, and supporting services. (NSSM)
• Manage Azure identity and application authentication, including Microsoft Entra ID (Azure AD), App Registrations, application permissions, OAuth-based authentication, and secure integration of applications with Azure services.
• Establish and maintain GitLab repositories, contributor access, branching/code-review workflows, GitLab Runners in VM, and CI/CD pipelines.
• Manage application PostgreSQL databases, including connectivity, migrations, backups, and deployment-related database changes.
• Initiate new projects, develop the initial technical implementation, establish coding and architecture standards, and onboard other developers for collaborative development.
• Maintain technical specifications, architecture documentation, deployment procedures, and operational documentation for applications.
• Leverage AI-assisted development tools such as Cursor and GitHub Copilot and develop reusable skills/instructions for AI coding assistants.
• Troubleshoot and resolve issues across the application, LLM-Gateway APIs, Application APIs, database, infrastructure, and deployment layers, collaborating with internal platform, security, and technology teams where required. Managing secrets and credentials through KeyVaults (TBD)

Your skills and experience

• 5-8Yrs experience in Python software development experience with Django, Flask, FastAPI, or equivalent frameworks.
• Experience building LLM/GenAI applications, RAG solutions, and AI agents using LangChain, LangGraph, or equivalent frameworks.
• Strong understanding of Git, GitLab, CI/CD, REST APIs, PostgreSQL, and application deployment.
• Working experience with cloud/virtualized infrastructure, preferably Azure and OpenStack.
• Experience with Nginx, HTTPS/TLS, Linux/Windows server environments, and application services.
• Working knowledge of React/JavaScript for maintaining web applications.
• Experience using AI-assisted coding tools such as Cursor, GitHub Copilot, or equivalent.
• Strong troubleshooting skills and the ability to independently take an application from requirement, design, development, deployment to production support.
• Strong appetite for continuous learning and experimentation, with the ability to independently explore emerging AI, software, cloud, and developer technologies, rapidly build proofs-of-concept, and identify opportunities to apply them to enterprise solutions.

Nice-To-Have

• Docker/Kubernetes, Terraform, Ansible, PowerShell.
• Azure AI/Azure OpenAI, vector databases/pgVector, MCP, and AI evaluation/observability, RAGAS RAG evaluation, ML, fine-tuning.
• Experience with enterprise identity, authentication, and security platforms.
• Experience with SharePoint, Power BI, Power Apps, and Microsoft Copilot Studio, including integration with enterprise applications, data sources, workflows, and AI-powered business solutions.