Responsibilities
- Build AI Agent Operations Center capabilities for agent registration, versioning, deployment tracking, run histories, incident triage, replay/debugging, trace correlation, and root-cause analysis.
- Develop agent workflows involving planning, tool execution, memory, retrieval-augmented generation, guardrails, and evaluations.
- Create operational dashboards for agent health metrics including success rate, latency, tool failure rate, cost per run, and loop detection.
- Instrument agent flows with OpenTelemetry and implement semantic conventions and tagging across prompts, tools, retrieval, responses, environments, tenants, and applications.
- Partner with SRE and observability teams on monitoring, alerting, and production readiness.
- Build and maintain automated testing, CI/CD, deployment, onboarding, scaffolding, and configuration capabilities for agent services and operations-center components.
- Collaborate with business, transformation, and AI platform teams to tailor scalable agents to domain requirements.
- Apply secure, reliable, scalable, and cost-effective deployment practices and support ongoing testing and validation of AI agents.
Requirements
- Bachelor’s degree in Computer Science, AI/ML, Data Science, or a related field.
- 3–5+ years of software engineering experience; 1+ years building and observing AI/ML or GenAI applications is preferred.
- Hands-on experience with agentic frameworks such as CrewAI, LangChain, Semantic Kernel, or AutoGen.
- Proficiency in Python and familiarity with APIs and microservices patterns.
- Strong experience with RAG patterns, including embeddings, vector search, retrieval evaluation, and chunking strategies.
- Experience with Azure, AWS, or GCP and containerized deployments using Kubernetes, AKS, or EKS.
- Familiarity with logs, metrics, traces, production troubleshooting, OpenTelemetry, distributed tracing, and telemetry pipelines.
- Experience building internal developer platforms or operational consoles with registries, run tracking, and dashboards.
- Experience with Azure AI Search or vector databases, prompt and version management, and evaluation frameworks.
- Knowledge of Responsible AI practices including data handling, safety guardrails, audit trails, and redaction strategies.
- Exposure to FinOps, token or GPU cost optimization, and chargeback or showback reporting.
- Ability to translate business challenges into technical solutions, collaborate cross-functionally, explain technical concepts to nontechnical stakeholders, and adapt to changing requirements.
Categories
About PepsiCo
PepsiCo is a playground for curious people. We invite thinkers, doers, and changemakers to champion innovation, take calculated risks, and challenge the status quo. From executives to team members on the front lines, we’re excited about the future. We take chances. Together, we dare to make the world a better place. Our associates are the magic ingredient. Each of them plays an integral role in helping create deep connections between people and our products. Think about your last group celebration: Chances are, one of our iconic brands was by your side. At PepsiCo, you’re invited to be a part of a global team of innovators who make, move, and sell these products—which are enjoyed by more than 1 billion people a day. A career at PepsiCo means working in a culture where everyone’s welcome. Here, you can dare to be yourself. No matter who you are or where you’re from, you can influence the people around you and the world at large. By showing up, you’ll have the opportunity to learn, develop and grow your skills for the future. Our supportive teams can fuel your professional goals to make a global impact on people and the planet. Join us. Dare for Better.