Senior Software Engineer

About the Role We are seeking a highly skilled Senior Software Engineer to design, configure, and build agentic AI systems and cloud-native software with ML-enabled capabilities. You will develop scalable software that leverages large language models, intelligent agents, workflow orchestration, APIs, cloud services, and MLOps practices to deliver secure, reliable AI-enabled solutions. What You'll Do

• Design, configure, and build agentic AI systems that can reason, plan, use tools, execute workflows, and interact with enterprise systems.
• Develop scalable software applications and services using modern cloud-native architectures.
• Integrate large language models, APIs, databases, vector stores, and orchestration frameworks into production-ready applications.
• Build and maintain AI-enabled workflows using agent frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, or similar technologies.
• Implement retrieval-augmented generation patterns, including document ingestion, chunking, embedding generation, vector search, reranking, and response generation.
• Partner with data science and ML teams to operationalize machine learning models and AI capabilities into software products.
• Apply MLOps practices for model deployment, monitoring, versioning, evaluation, governance, and continuous improvement.
• Develop reusable components, APIs, services, and integration patterns to accelerate AI solution delivery.
• Define and implement robust cloud architectures, preferably on AWS, using serverless, containerized, or microservices-based approaches.
• Implement observability, logging, monitoring, error handling, and performance optimization for AI and ML-enabled applications.
• Evaluate and improve agent performance, including prompt quality, tool selection, response accuracy, latency, cost, and reliability. What We're Looking For
• Proven senior software engineer with strong experience in agentic AI systems, cloud-native software, and ML-enabled solutions.
• Hands-on experience with agent frameworks and retrieval-augmented generation, including model integration, evaluation, deployment, monitoring, and automation.
• Experience integrating large language models with APIs, databases, vector stores, and orchestration frameworks.
• Experience building AI workflows using agent frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, or similar.
• Proficiency in MLOps practices: deployment, monitoring, versioning, governance, and continuous improvement.
• Ability to work with cross-functional teams and stakeholders to deliver secure, reliable software products.
• Strong problem-solving, communication, and collaboration skills.
• Familiarity with AWS, serverless, containers, and microservices is a plus.