Software Engineer - AI /ML

Job Description: You will be responsible for developing software and machine learning solutions, particularly in building agentic AI systems and autonomous workflows. Your strong proficiency in Python and software engineering best practices will be crucial in this role. Additionally, you will need experience with LLM APIs such as OpenAI, Anthropic Claude, and Azure OpenAI. Understanding of prompt engineering, prompt chaining, and few-shot learning will be required. Familiarity with tool use, function calling, and agent frameworks is essential. Knowledge of retrieval-augmented generation (RAG) and vector databases is also necessary. You should have experience with API integration and asynchronous programming, and be comfortable with experimentation and iterative development. Qualifications Required: - 2-5 years of software development or machine learning experience - Hands-on experience building agentic AI systems or autonomous workflows - Strong proficiency in Python and software engineering best practices - Experience with LLM APIs (OpenAI, Anthropic Claude, Azure OpenAI, etc.) - Understanding of prompt engineering, prompt chaining, and few-shot learning - Familiarity with tool use, function calling, and agent frameworks - Knowledge of retrieval-augmented generation (RAG) and vector databases - Experience with API integration and asynchronous programming - Comfortable with experimentation and iterative development Preferred Qualifications: - Experience with specific agentic frameworks (LangChain, CrewAI, Autogen, Semantic Kernel) - Cloud platform experience (Azure, AWS, or GCP) for AI/ML services - Background in building production ML systems with monitoring and observability - Experience with fine-tuning or customizing LLMs - Knowledge of agent evaluation frameworks and bench-marking - Familiarity with DevOps practices for ML systems - Experience in enterprise software or complex system integration Nice to Have: - Experience with multi-agent systems and agent communication patterns - Background in knowledge graphs or semantic search - Experience building chatbots or conversational AI systems - Understanding of token optimization and cost management for LLM applications - Published work, contributions to open-source AI projects, or technical writing Job Description: You will be responsible for developing software and machine learning solutions, particularly in building agentic AI systems and autonomous workflows. Your strong proficiency in Python and software engineering best practices will be crucial in this role. Additionally, you will need experience with LLM APIs such as OpenAI, Anthropic Claude, and Azure OpenAI. Understanding of prompt engineering, prompt chaining, and few-shot learning will be required. Familiarity with tool use, function calling, and agent frameworks is essential. Knowledge of retrieval-augmented generation (RAG) and vector databases is also necessary. You should have experience with API integration and asynchronous programming, and be comfortable with experimentation and iterative development. Qualifications Required: - 2-5 years of software development or machine learning experience - Hands-on experience building agentic AI systems or autonomous workflows - Strong proficiency in Python and software engineering best practices - Experience with LLM APIs (OpenAI, Anthropic Claude, Azure OpenAI, etc.) - Understanding of prompt engineering, prompt chaining, and few-shot learning - Familiarity with tool use, function calling, and agent frameworks - Knowledge of retrieval-augmented generation (RAG) and vector databases - Experience with API integration and asynchronous programming - Comfortable with experimentation and iterative development Preferred Qualifications: - Experience with specific agentic frameworks (LangChain, CrewAI, Autogen, Semantic Kernel) - Cloud platform experience (Azure, AWS, or GCP) for AI/ML services - Background in building production ML systems with monitoring and observability - Experience with fine-tuning or customizing LLMs - Knowledge of agent evaluation frameworks and bench-marking - Familiarity with DevOps practices for ML systems - Experience in enterprise software or complex system integration Nice to Have: - Experience with multi-agent systems and agent communication patterns - Background in knowledge graphs or semantic search - Experience building chatbots or conversational AI systems - Understanding of token optimization and cost management for LLM applications - Published work, contributions to open-source AI projects, or technical writing