14 hours ago
Hyderābād, IndiaMid Level / Senior
Responsibilities
- Build AI Agent Operations Center capabilities for agent registration, versioning, deployment tracking, run histories, replay, debugging, trace correlation, and root-cause analysis.
- Develop agent workflows covering planning, tool execution, memory, retrieval-augmented generation, guardrails, and evaluations.
- Create dashboards and operational views for agent health, including success rate, latency, tool failures, cost per run, and loop detection.
- Instrument agent flows end-to-end with OpenTelemetry and implement semantic conventions and tagging standards.
- Partner with SRE and observability teams on monitoring, alerting, incident triage, and production readiness.
- Build and maintain automated testing, deployment, CI/CD, and onboarding automation for agent services and operations-center components.
- Collaborate with AI platform, data science, engineering, IT, product, transformation, and business stakeholders to deliver cross-domain agents.
- Apply responsible AI, reliability, security, scalability, and FinOps practices to agent deployments.
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 generative AI applications is preferred.
- Hands-on experience with agentic frameworks such as Crew.ai, 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, 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 token or GPU cost optimization and chargeback or showback reporting.
- Ability to design agent orchestration, apply testing and automation discipline, support incident response, translate business challenges into technical solutions, and communicate complex concepts to nontechnical stakeholders.
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About PepsiCo
PepsiCo is a global food and beverage company that manufactures, markets, and distributes snacks and drinks under brands such as Pepsi, Mountain Dew, Gatorade, Lay’s, Doritos, and Quaker Oats. It sells to consumers through retail, foodservice, and e-commerce channels, with products available in more than 200 countries and territories. Founded in 1965 and headquartered in Purchase, New York, PepsiCo is a public company listed on NASDAQ under the symbol PEP.