IND Senior Staff Software Engineer
Description
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
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Develop Algorithms that enable AI agents to perform tasks without step-by-step instructions.
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Design and implement agentic AI systems capable of autonomous decision-making, learning from experience, and adapting to dynamic goals and contexts
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Design and develop multi-agent frameworks using tools such as LangGraph , Crew AI, or Semantic Kernel to orchestrate intelligent workflows.
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Design and develop machine learning techniques that allow agents to learn from experience and adapt over time.
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Translate business requirements into agentic AI solutions.
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Collaborate with data scientists, software engineers, business stakeholders, and product teams to integrate AI solutions into production systems.
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Conduct context and prompt engineering using zero-shot, few-shot, and chain-of-thought techniques to enhance model performance and relevance.
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Optimize agents based on different models for performance, scalability, and accuracy.
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Ensure ethical AI practices and compliance with data privacy regulations.
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Document processes, models, and code for transparency and reproducibility.
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Conduct research and stay up to date with the latest advancements in AI/ML technologies.
Required Skills & Experience
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Proficiency in programming languages such as Python, Java, or C++.
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Strong foundation in AI/ML algorithms, data structures, and software engineering principles.
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Understanding of cloud platforms (e.g., AWS, Azure, GCP) for deploying AI solutions.
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Familiarity with MLOps tools and practices (e.g., MLflow , Kubeflow, Docker for CI/CD).
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Solid knowledge of data structures, algorithms, and software engineering principles.
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Experience with agent orchestration, LLMOps , and model lifecycle management, vector search, information retrieval, graph algorithms and knowledge grap h.
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Experience with version control systems (e.g., Git).
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Familiarity with agent orchestration platforms and enterprise integration.
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Strong problem-solving skills and ability to work independently and collaboratively.
Preferred Skills & Experience
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Experience with natural language processing (NLP), computer vision, or reinforcement learning.
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Knowledge of generative AI and foundation models (e.g., Gemini, Claude).
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Experience with real-time inference systems and edge AI.
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Background in mathematics, statistics, or computational neuroscience.
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Understanding of LLM (Large Language Model) & LRM (Large Reasoning Model)
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Understanding of AI ethics, bias mitigation, and explainable AI.
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