Principal AI Engineer - Agent Ops / SRE Locations (Hybrid) - Hartford, CT - Columbus, OH - Charlotte, NC - Chicago, IL 100% Remote USA Full time 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. The Hartford’s applied AI COE Team is seeking a Principal AI Engineer - Agent Ops/SRE. The AI-COE serves as a centralized function to accelerate AI maturity, eliminate silos, and streamline AI adoption through standardized processes and technologies, ensuring strong alignment with business objectives. AI-COE is responsible for building reusable AI solutions, horizontal AI Agents, Agent Starter Packs and partnering with other IT/Business unit to deliver and maintain their AI Assets. This role will support data scientist and AI solution engineer to build, deploy & maintain AI-COE products, ensuring reliability, uptime and throughput as per application tiers. This is the most senior individual contributor role, responsible for driving efficiency across the AI delivery lifecycle (AgentOps), while applying strong software and systems engineering practices to scale, operate, and ensure reliability of AI systems (SRE). You will work very closely with AI platform , Cloud Engineering, Security and Enterprise SRE team using their standards and tooling to deploy and maintain the solution. This role requires versatility across DevOps, MLOps, AgentOps, and SRE, with strong expertise in automation and a proven track record of building and operating large-scale, mission-critical systems. If you are passionate about automation and building large-scale distributed systems, we’d love to connect with you. Responsibilities: - Serve as technical liaison between AI COE and Platform Engineering & Enterprise SRE teams. - Ensure AI systems meet requirements for performance, latency, throughput, resiliency, recovery, observability and reliability. - Partner with AI engineers, Applied AI Scientist, and AI Architects to design, build and maintain scalable, fault tolerant AI systems as per SLO. - Partner with Platform engineering team to design and implement CICD, GITOps, and IAC (Terraform) modules. Making sure we use our AgentOps NSA, standards, Ref. architecture and tooling. - Partner with enterprise release management and AI Governance team to build & deploy AI solutions using their platform tooling. Supporting entire AI lifecycle as per the standard work template. - Build standardized deployment templates, reference architecture, automation scripts, terraform modules, CICD pipelines, and operational runbooks for AI workloads. - Design and build IDP (Harness) catalogs, templates & pipelines partnering with enterprise platform engineering team. - Manage production systems to ensure our enterprise SLOs are met. - Manage incident response for production systems, including triaging, escalating, RCA and implementing corrective actions. Qualifications: - Bachelor's degree in Computer Science, Computer Engineering, or a technical field. - 10+ years building and shipping software and/or platform solutions for enterprises. - Programming experience with Python is required. - 3+ years of experience with IAC (Terraform). - 5+ years of experience owning production CICD, GitOps and release management gating. - 3+ years of experience in implementing observability, performance & reliability solutions: SLO, P99-95 latency, alert tuning, & dashboards. - Experience with AI observability/monitoring tools such as Dynatrace, Splunk, Arize & OpenTelemetry/OpenInference is must. - Proven experience with Google's Gemini Enterprise Agent platform is a plus. - Experience with GKE/Docker/Registry is a plus. - Proven experience in working with other cloud providers such as AWS cloud is a plus. - Experience with Automated Testing, Automated Deployments, Agile methodologies, Unit Testing, and Integration Testing tools. - Conversational UX/UI design (multi-turn chatbots) and Human-Agent-Interaction (HAI) is a plus. - Experience with IR, vector embedding, and Hybrid/Semantic search technologies. - Experience with LLM orchestration frameworks like Langchain, LlamaIndex, LangSmith, LangGraph, Google Agent Development Kit, is a plus. - Experience with Generative AI Guardrails, responsible AI, adversarial attack mitigation, and red teaming is a plus. - Foundational understanding of Natural Language Processing and Deep Learning. - Excellent problem-solving skills and the ability to work in a collaborative team environment. - Excellent communication skills. This role can have a Hybrid or Remote work arrangement. Candidates who live near one of our office locations (Hartford, CT, Charlotte, NC, Chicago, IL, Columbus, OH) will have the expectation of working in an office 3 days a week (Tuesday through Thursday) Candidates who do not live near an office will have a remote work arrangement, with the expectation of coming into an office as business needs arise. Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position Compensation The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is: $168,400 - $220,000