IND Senior Staff Software Engineer

IND Senior Staff Software Engineer - GCC020
We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.

Key Responsibilities

• Develop Algorithms that enable AI agents to perform tasks without step-by-step instructions.

• Design and implement agentic AI systems capable of autonomous decision-making, learning from experience, and adapting to dynamic goals and contexts

• Design and develop multi-agent frameworks using tools such as LangGraph , Crew AI, or Semantic Kernel to orchestrate intelligent workflows.

• Design and develop machine learning techniques that allow agents to learn from experience and adapt over time.

• Translate business requirements into agentic AI solutions.

• Collaborate with data scientists, software engineers, business stakeholders, and product teams to integrate AI solutions into production systems.

• Conduct context and prompt engineering using zero-shot, few-shot, and chain-of-thought techniques to enhance model performance and relevance.

• Optimize agents based on different models for performance, scalability, and accuracy.

• Ensure ethical AI practices and compliance with data privacy regulations.

• Document processes, models, and code for transparency and reproducibility.

• Conduct research and stay up to date with the latest advancements in AI/ML technologies.

• Proficiency in programming languages such as Python, Java, or C++.

• Strong foundation in AI/ML algorithms, data structures, and software engineering principles.

• Understanding of cloud platforms (e.g., AWS, Azure, GCP) for deploying AI solutions.

• Familiarity with MLOps tools and practices (e.g., MLflow , Kubeflow, Docker for CI/CD).

• Solid knowledge of data structures, algorithms, and software engineering principles.

• Experience with agent orchestration, LLMOps , and model lifecycle management, vector search, information retrieval, graph algorithms and knowledge grap h.

• Experience with version control systems (e.g., Git).

• Familiarity with agent orchestration platforms and enterprise integration.

• Strong problem-solving skills and ability to work independently and collaboratively.

• Experience with natural language processing (NLP), computer vision, or reinforcement learning.

• Knowledge of generative AI and foundation models (e.g., Gemini, Claude).

• Experience with real-time inference systems and edge AI.

• Background in mathematics, statistics, or computational neuroscience.

• Understanding of LLM (Large Language Model) & LRM (Large Reasoning Model)

• Understanding of AI ethics, bias mitigation, and explainable AI.