PepsiCo
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Hyderabad · On-site · 3-6 Yrs · Oct 21
Food & Beverage Manufacturing · 10000+ Employees · Purchase, US
PepsiCo is a global food and beverage leader with a product portfolio including 22 brands that generate more than $1 billion each in annual retail sales. Our main businesses – Quaker, Tropicana, Gatorade, Frito-Lay and Pepsi-Cola – make hundreds of enjoyable foods and beverages that are loved throughout the world. At PepsiCo, you get the best of both worlds: an entrepreneur’s mindset plus reach and resources. Our collaborative culture and worldwide presence generate a stream of new opportunities to define the future and propel your life’s work. Bring your unique perspective. Bring curiosity. Bring ingenuity, and drive. We’ll give you a platform to be daring on a global scale.
Hiring: Engineering, Human resources
What employees say
+ Good work life balance, hibrid mode is very convenient, pay is better
− Mangers are worst, too much micro management
More reviews on the company profile.
Interview experience · Senior Software QA Engineer
I recently interviewed with PepsiCo and successfully cleared one round. I then went through two technical interview rounds, expecting a professional discussion around my experience, technical skills, and problem-solving
Difficult difficulty · New Delhi · 211 reports
More interview insightsJob description
Overview
The AI Observability Engineer (Agentic Frameworks & AI Agent Operations Center Developer) builds and operationalizes agentic AI solutions using modern orchestration frameworks and contributes to an AI Agent Operations Center that enables safe, reliable, and observable agent behavior at scale.
Responsibilities
- AI Agent Operations Center (70%)• Build “operations center” capabilities for agent runtime management: agent registry, versioning, deployment tracking, and run histories
- Enable operational workflows such as incident triage, replay/debug runs, trace correlation, and root-cause analysis across agent steps
- Implement operational dashboards and views for agent health: success rate, latency, tool failure rate, cost per run, and loop detection
- Instrument agent flows end-to-end using OpenTelemetry (or equivalent), enabling correlation across prompts, tool calls, retrieval, and responses
- Implement semantic conventions and tagging standards (agent name/version, tool name, model provider, environment, tenant/app)
- Partner with SRE/observability teams to ensure production-grade monitoring, alerting, and operational readiness
- Collaboration with Teams (10%)• Collaborate with transformation teams and business stakeholders to understand requirements and tailor AI agents to specific domains.
- Work closely with AI platform teams to build scalable and cross-domain AI agents while ensuring end-to-end observability.
- Integration & Deployment (10%)• Build and maintain CI/CD pipelines for agent services and operations center components, including automated testing and deployment
- Automate onboarding for new agent use cases (templates, scaffolding, configuration checks)
- Drive best practices for secure, scalable, and cost-effective agent deployments
- Continuous Learning (10%)• Stay updated with the latest advancements in AI and machine learning technologies and integrate these into existing or new AI agents.
- Conduct thorough testing and validation to ensure the reliability and accuracy of AI agents and solutions.
- Decision-Making Autonomy Moderate – Significant autonomy in the technical aspects of AI model development and implementation, working under the strategic direction provided by the Senior AI Solutions leads.
- Supervision Required Moderate – Operates with general guidance from the Senior AI Solutions leads, with regular updates for alignment and support.
- Complexity of Role High – The role requires managing complex AI/ML projects, working with large datasets, and ensuring successful integration with existing systems while maintaining scalability.
- Cross-Functional Interactions Yes – Regular interaction with Data Science, Engineering, IT, digital products and business stakeholders to ensure effective AI solution Observability.
Qualifications
- Key Skills/Experience Required
- Education: Bachelor’s in Computer Science, AI/ML, Data Science, or a related field.
- Experience: 3–5+ years of software engineering experience; 1+ years building and observe AI/ML or GenAI applications preferred
- Required Expertise:
- Hands-on experience with agentic frameworks (Crew.ai, LangChain, Semantic Kernel, AutoGen, or similar)
- Proficiency in Python (primary) and familiarity with APIs/microservices patterns
- Strong experience with RAG patterns (embeddings, vector search, retrieval evaluation, chunking strategies)
- Experience with cloud environments (Azure/AWS/GCP) and containerized deployments (Kubernetes/AKS/EKS)
- Familiarity with observability fundamentals (logs/metrics/traces) and production troubleshooting
- Experience building internal developer platforms or operational consoles (agent registry, run tracking, dashboards)
- Familiarity with OpenTelemetry, distributed tracing, and telemetry pipelines
- Experience with Azure AI Search / vector databases, prompt/version management, and evaluation frameworks
- Knowledge of Responsible AI practices: data handling, safety guardrails, audit trails, and redaction strategies
- Technical Proficiency: Agent orchestration design (planning, tool execution, memory, RAG), Strong engineering discipline: testing, versioning, CI/CD, automation, Operational mindset: reliability, debuggability, and incident response support
- Problem-Solving: Ability to translate business challenges into technical solutions.
- Collaboration Skills: Effective at working within cross-functional teams.
- Agility: Flexibility to adapt to changing requirements and new technologies.
- Communication Skills: Capable of explaining complex technical concepts to non-technical stakeholders.
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Job application FAQ
Last updated 5 November 2026
- How do I apply for AI Platforms Engineer at PepsiCo?
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- Is AI Platforms Engineer remote or on-site in Hyderabad, Telangana?
- This listing is marked on_site with location Hyderabad, Telangana. Confirm details on the job description before applying.
- What skills matter for this AI Platforms Engineer role at PepsiCo?
- This is a mid-level AI Platforms Engineer role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.