The role focuses on developing GenAI, Agentic AI, and RAG-based applications that improve business processes, document intelligence, knowledge management, and commercial operations.

You will collaborate with architects, product teams, and business stakeholders to deliver scalable, secure, and production-ready AI solutions.

Key Responsibilities :

- Design, develop, and deploy LLM-powered applications and AI services.

- Build and optimize RAG pipelines, including document ingestion, embeddings, vector search, and response grounding.

- Develop agentic workflows using frameworks such as LangChain, Semantic Kernel, AutoGen, or similar tools.

- Build APIs and backend services using Python, FastAPI, Azure Functions, and containerized environments.

- Implement solutions using Azure OpenAI, Azure AI Studio, Azure AI Search, and related AI platforms.

- Integrate AI capabilities with enterprise systems, workflows, and business applications.

- Implement monitoring, logging, and observability using Azure Monitor, OpenTelemetry, Datadog, or similar tools.

- Participate in design reviews, testing, deployment, and production support.

- Create reusable AI assets, prompt templates, and engineering accelerators.

- Continuously improve performance, reliability, scalability, and cost efficiency of AI solutions.

Required Qualifications :

- 4-6 years of experience in Software Engineering, AI/ML Engineering, or AI Solution Development.

- Hands-on experience building and deploying GenAI or LLM-powered applications.

- Strong expertise in Python and backend application development.

- Experience with Azure OpenAI, OpenAI APIs, Azure AI Studio, AWS Bedrock, Vertex AI, or similar platforms.

- Strong understanding of RAG, embeddings, vector databases, and semantic search.

- Experience with LangChain, Semantic Kernel, AutoGen, or equivalent orchestration frameworks.

- Experience with Azure Functions, FastAPI, Docker, GitHub, and Azure DevOps.

- Knowledge of CI/CD, containerization, automated testing, and secure deployment practices.

- Familiarity with monitoring and observability platforms.

- Strong problem-solving, communication, and stakeholder collaboration skills.

Preferred Qualifications :

- Experience with multi-agent systems and advanced AI workflow orchestration.

- Exposure to MCP, A2A communication, or distributed agent architectures.

- Familiarity with Microsoft AI Foundry, Azure ML, or Copilot Studio.

- Experience with enterprise integrations, API management, and event-driven architectures.

- Knowledge of AI governance, model evaluation, prompt safety, and cost optimization.

- Working knowledge of TypeScript or C# is an advantage.

- Experience supporting AI products in a build-own-operate environment.

What We're Looking For :

- Strong engineering mindset with a passion for AI-driven products.

- Ability to convert business requirements into scalable technical solutions.

- Excellent collaboration and communication skills.

- Ownership-driven professional focused on quality, innovation, and continuous improvement.