IND Staff Software Engineer - GCC122 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. Position Overview We are seeking an AI/ML Engineer who will be responsible for architecting, building and deploying production-grade AI systems This is a highly hands-on role requiring deep expertise in ML engineering, MLOps, LLM architecture, and Generative/Agentic AI concepts and tooling exposure. This role is well-suited for someone who brings intellectual curiosity, a bias toward action, and a collaborative mindset, and who is looking to deepen their AI/ML engineering expertise while taking on increasing responsibility over time________________________________________ Key

Responsibilities

• Design and implement production-grade AI/ML and Agentic AI solutions that drive end-to-end transformation across pricing, underwriting, and sales. • Partner with Cloud, AIOps, Data Science, LOB IT, Enterprise Architecture, and Data teams to provision infrastructure, deploy services, and operate scalable AI platforms using modern DevOps practices. • Leverage AI Platform, agent development standards, and agent frameworks to build, deploy, monitor and maintain agentic solutions & AI/ML pipelines. • Architect and build highly available, scalable, secure, and fault-tolerant AI/ML systems, applying modern distributed system patterns such as event-driven, pub/sub, and point-to-point architectures. • Design and implement agent memory, evaluation, and feedback mechanisms to enable quality, safety, and reliability-driven tuning and continuous improvement. • Develop advanced context engineering, adaptive prompting, multi-agent coordination, and RAG/Agentic RAG systems using techniques such as HyDE, RAPTOR, and GraphRAG to improve accuracy and relevance. • Write high-quality, production-ready Python (e.g., asyncio, FastAPI, Pydantic) and instrument AI observability using OpenTelemetry, offline evaluation, and drift monitoring, while leveraging enterprise AI platforms and standards. ________________________________________ Required Skills &

Experience

Experience

Range - 6 to 9 Years • Bachelor’s or Master’s degree in computer science , Software Engineering, Data Science, or a closely related discipline. • Professional experience in ML, Software Engineering, or a related role, including 3+ years delivering AI/ML solutions in production. • Strong Python development experience, building and operating production services and APIs. Generative AI & Agentic Systems •

Experience

developing full-stack agentic solutions using agent frameworks such as ADK, A2A, MCP, LangChain, LangGraph, or CrewAI, and familiarity with commercial and open-source foundation models. •

Experience

building and operating advanced RAG and Agentic RAG systems using modern techniques and methodologies. •

Experience

with agentic monitoring, observability, and model evaluation frameworks to assess quality, safety, and performance in production. ML, Platforms & Cloud • Hands-on experience with ML and AI frameworks such as PyTorch, Hugging Face, Pandas, NumPy, and related libraries. • Hands-on experience with at least one public cloud AI/GenAI platform (e.g., AWS SageMaker/Bedrock or Google Vertex AI, Vertex AI Search, and RAG Engine). Software Engineering, DevOps & Security •

Experience

designing and delivering production-grade APIs and microservices using modern software engineering practices. • Hands-on experience with DevOps and CI/CD pipelines, infrastructure as code (e.g., Terraform), GitHub collaboration, and cloud deployments. •

Experience

with DevSecOps tools such as Nexus, SonarQube, Checkmarx, and mcp-scan. Ways of Working & Communication •

Experience

working in lean, agile environments (e.g., SAFe or similar frameworks). • Strong communication and collaboration skills, with the ability to explain complex technical concepts to technical and non-technical stakeholders, influence decisions, and work effectively across teams. ________________________________________Nice to Have • Knowledge of automated testing, validation gates, canary deployments, and rollback strategies for ML and Agentic AI systems. •

Experience

designing and implementing data pipelines for ML and Agentic AI workloads using modern data platforms (e.g., Snowflake, Airflow, S3/Glue/EMR/Redshift, Apache Iceberg, or equivalent). •

Experience

working in insurance or other regulatory environments. • Ability to partner with governance, risk, compliance, and security teams to ensure responsible AI through techniques such as bias mitigation, disparate impact analysis, and counterfactual testing.

About Us

| Our Culture | What It’s Like to Work Here Every day, a day to do right. Showing up for people isn’t just what we do. It’s who we are – and have been for more than 200 years. We’re devoted to finding innovative ways to serve our customers, communities and employees—continually asking ourselves what more we can do. Is our policy language as simple and inclusive as it can be? Can we better help businesses navigate our ever-changing world? What else can we do to destigmatize mental health in the workplace? Can we make our communities more equitable? That we can rise to the challenge of these questions is due in no small part to our company values that our employees have shaped and defined. And while how we contribute looks different for each of us, it’s these values that drive all of us to do more and to do better every day.

About Us

Our Culture What It’s Like to Work Here Perks &

Benefits

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