Sr. AI DevOps Developer

• Design and develop custom AI agents, GenAI applications, and AI-powered automation based on client business requirements.
• Develop, test, deploy, monitor, and continuously enhance AI solutions across development and production environments.
• Work with client stakeholders to translate business requirements into practical AI solutions.
• Implement and maintain RAG pipelines, prompt engineering, agentic workflows, tool/function calling, and LLM integrations.
• Provide ongoing DevOps and production support, including monitoring, troubleshooting, performance optimization, upgrades, and incident resolution.
• Build and maintain CI/CD pipelines and automated deployment processes.
• Evaluate emerging AI models, frameworks, and technologies and recommend appropriate solutions for client projects.

Core Skillsets

• Strong hands-on experience developing applications using Generative AI and LLMs
• Experience with AI agents / agentic AI, including multi-step workflows, tool/function calling, orchestration, and autonomous task execution.
• Strong knowledge of RAG architecture, including document processing, chunking, embeddings, vector search, retrieval strategies, and context management.
• Strong prompt engineering skills, including prompt optimization, structured outputs, few-shot prompting, and hallucination mitigation.
• Experience with LLM platforms such as OpenAI / Azure OpenAI, Anthropic, Google Gemini, AWS Bedrock, or equivalent.
• Understanding of LLM evaluation, AI application testing, model selection, token/cost optimization, latency, and scalability.
• Experience integrating LLMs with enterprise applications, APIs, databases, and business processes.
• Knowledge of AI security considerations including prompt injection, data privacy, PII protection, access control, and responsible AI.

• Strong programming experience in Python; Java, JavaScript/TypeScript, or C# is a plus.
• Experience developing REST APIs, backend services, microservices, and enterprise integrations.
• Experience with Git, CI/CD, Docker, and cloud environments such as Azure, AWS, or GCP.
• Experience troubleshooting and supporting applications in production.