Principal AI Engineer - Agent Ops / SRE
About The Position
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.
Requirements
- 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.
- Excellent problem-solving skills and the ability to work in a collaborative team environment.
- Excellent communication skills.
- 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
Nice To Haves
- 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.
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.
Benefits
- short-term or annual bonuses
- long-term incentives
- on-the-spot recognition
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What This Job Offers
Job Type
Full-time
Career Level
Principal
