Sr Software Engineer - Gen AI

IND Senior Software Engineer - GCC123
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T8 AI Engineer – Small Commercial IT (India GCC)
The Hartford’s Small Commercial IT Team is seeking a highly motivated and experienced T8 AI Engineer (Individual Contributor) to help build and operationalize Generative AI (GenAI) and Agentic AI capabilities within enterprise applications. This role contributes to Hartford’s Enterprise AI Platform powered by Google Cloud Vertex AI, providing a unified, secure, enterprise-ready foundation to scale responsible AI across the organization.
This position requires hands-on engineering experience building agentic systems—AI agents that reason, orchestrate workflows, and interact with enterprise systems—using Vertex AI components such as Gemini foundation models, Agent Development Kit (ADK), and Agent Engine. The role also leverages platform capabilities including prompt management, observability, evaluation pipelines, and security controls such as Model Armor.
You will work in an Agile environment and collaborate across product teams, platform teams, and data science partners to deliver measurable business outcomes through intelligent automation, decision support, and enhanced user experiences.
Responsibilities
Design and implement AI-enabled software services that are scalable, fault-tolerant, secure, and maintainable, aligned with enterprise engineering standards.
Build and integrate agentic AI capabilities into enterprise applications using Hartford’s Vertex AI-based platform, including agent workflows, tool integration, and orchestration patterns.
Develop agent solutions leveraging Gemini foundation models for advanced reasoning and multimodal GenAI capabilities.
Use the Agent Development Kit (ADK) to define agent behaviors, workflows, and multi-agent patterns with fine-grained control.
Deploy, scale, and operate agents in production using Agent Engine, including monitoring, logging, tracing, and session management.
Implement retrieval-augmented generation (RAG) patterns using vector databases and embeddings to ensure relevance and accuracy of AI outputs.
Apply prompt engineering and prompt lifecycle management using centralized governance to ensure consistent, reusable, and compliant prompt assets.
Partner with Data Science and Architecture teams to implement AI-powered features using large language models, embeddings, vector databases, orchestration frameworks, and evaluation strategies.
Operationalize AI safely and responsibly by applying platform guardrails, security controls, and responsible AI governance practices.
Build observability and evaluation into AI systems by capturing logs, metrics, and traces across agent workflows and applying evaluation pipelines to measure correctness, completeness, and safety.
Contribute to LLM upgrade readiness, including version migration testing, regression strategies, automation, and change management to minimize delivery disruption.
Troubleshoot complex issues across application, data, and AI layers, communicating risks and mitigations clearly and proactively.
Contribute to knowledge sharing and reusable accelerators within the India GCC.
Qualifications
Bachelor’s degree in Computer Science, Engineering, or a related technical field; advanced degree preferred.
Strong software engineering experience designing and delivering enterprise applications and services, including APIs, distributed systems, and cloud-native architectures.
Hands-on experience with Google Cloud Vertex AI–based GenAI development across the full lifecycle from development through production operations.
Hands-on experience with foundational engineering tech stacks, such as; Python, Node.js, Java/Spring, CI/CD pipelines, and modern UI frameworks like Angular or React
Experience designing or implementing Generative AI solutions using large language models, prompt engineering, and retrieval-augmented generation.
Familiarity with agentic AI systems and orchestration frameworks, including ADK for agent development and Agent Engine for production runtime operations.
Understanding of responsible AI practices, including model evaluation, governance controls, and safe deployment guardrails.
Strong written and verbal communication skills, with the ability to collaborate effectively across engineering, product, and data science teams.
Preferred / Nice-to-Have
Experience building or integrating systems with embeddings, vector databases, and agent patterns such as summarization, classification, recommendation agents, and LLM-based evaluation.
Experience with enterprise operational readiness for agentic solutions, including incident triage, SLAs, release readiness, and run-ops support.
Experience contributing to standardized templates, frameworks, or accelerators that enable faster AI solution provisioning and reuse.

Work arrangement
No