Fastapi Developer Jobs in Oak Lawn, IL (NOW HIRING)

Job Summary:
PepsiCo is a leading global food and beverage company, seeking a Lead AI Engineer specializing in Agentic AI enablement. The role involves leading the design and delivery of production-grade agent capabilities, ensuring solutions scale across diverse environments while collaborating with transformation teams and platform engineering.
Responsibilities:
• Architect and deploy transformative AI agent solutions directly in client environments, adapting core technologies to unique client constraints and infrastructure. (Lead/Execute)
• Rapidly customize agent patterns (tool integrations, enterprise system connections, security models) to solve high-impact business challenges across diverse client tech stacks. (Lead/Execute)
• Transform ambiguous client requirements into production-ready solutions with minimal iterations through exceptional technical discovery skills. (Lead)
• Drive on-site performance optimization beyond client expectations (latency, reliability,throughput) while working within client infrastructure limitations. (Execute/Lead)
• Establish implementation playbooks that accelerate future deployments and enable customer success teams to scale. (Lead)
• Design and implement BU and function-specific evaluation frameworks that validate solution effectiveness in production environments with real data. (Lead/Execute)
• Develop rapid diagnostic methodologies to identify and resolve critical issues during implementation without disrupting client operations. (Execute/Lead)
• Create monitoring systems that provide early warning of edge cases and performance degradation unique to each deployment environment. (Execute)
• Perform advanced troubleshooting in constrained client environments where standard tools may be unavailable. (Execute/Lead)
• Establish quality baselines that enable clients to self-monitor system health post- implementation. (Execute/Lead)
• Fine-tune model selection and routing strategies based on function-specific data characteristics and performance requirements. (Lead/Execute)
• Optimize prompt engineering for unique BU domains, creating specialized techniques that overcome domain-specific challenges. (Execute/Lead)
• Implement model adaptation techniques that improve performance with minimal additional client data. (Execute)
• Develop function-ready evaluation frameworks that demonstrate model effectiveness to technical and business stakeholders. (Lead)
• Lead complex integrations between AI capabilities and diverse client systems (ERPs, CRMs, legacy databases, custom applications). (Lead/Execute)
• Design and implement secure data pipelines that respect client compliance requirements while enabling AI functionality. (Execute/Lead)
• Create adapter patterns that isolate core AI functionality from client-specific integration complexities. (Lead)
• Develop client-specific documentation and knowledge transfer protocols that enable client teams to maintain integrations independently. (Execute/Lead)
• Serve as the primary technical bridge between core engineering and client stakeholders, translating between business needs and technical capabilities. (Lead)
• Mentor client technical teams to build internal AI implementation capabilities. (Lead)
• Drive adoption through hands-on workshops, knowledge transfer sessions, and executive-level capability demonstrations. (Lead/Execute)
• Identify expansion opportunities through deep understanding of client's technical landscape and business challenges. (Lead)
• Communicate complex technical concepts effectively to diverse audiences from C-suite to implementation teams. (Lead)
Qualifications:
Required:
• Bachelor’s in CS/AI/ML required or equivalent experience.
• 12+ year experience with Software life cycle
• Expertise in ML (structured and unstructured data) development and engineering
• Proven experience shipping LLM/agent solutions to production with measurable quality and operational practices.
• Advanced Software Engineering: Python (and Java) mastery with distributed systems expertise; performance optimization (profiling, parallelization); architecture patterns (e.g., FastAPI, asyncio, Pydantic)
• LLM & Agent Systems: Multi-agent orchestration (LangChain, LangGraph, CrewAI); advanced prompt engineering; custom agent memory architectures; model optimization techniques
• Evaluation Framework Development: Statistical evaluation design (confidence intervals, power analysis); benchmark creation; instrumentation frameworks (e.g., MLflow, Arise); regression testing systems
• ML Operations: Production deployment pipelines (Docker, Kubernetes, Ray); model registry management; scaled inference optimization; GPU utilization optimization
• System Architecture: Microservice design patterns; high-throughput event processing; fault-tolerance implementation; horizontal scaling architectures
• Technical Leadership: Architecture governance systems; engineering standards development; build-vs-buy evaluation frameworks; technical roadmap creation
• Adaptive Development: Rapid prototyping; cross-platform implementation; client environment adaptation (air-gapped deployment, legacy system integration)
• Field Implementation: On-site deployment automation; custom agent development for specific domains; real-time system tuning; client-specific orchestration patterns
• Function-Centric Evaluation: Business KPI measurement frameworks; domain-specific benchmarking; hybrid test harnesses; real-world validation methodologies
• Enterprise Integration: Data Warehouse, Data Lake and Legacy system connectors (SAP, Oracle, Salesforce); secure data pipeline development; custom API wrapper creation; compliance-aware integration patterns
• Infrastructure Adaptation: On-premises AI deployment; private cloud implementation (Azure Stack, AWS Outposts); edge computing optimization; security-constrained architectures
• Implementation Diagnostics: Real-time debugging in production; performance profiling in restricted environments; root cause analysis methodologies; custom monitoring solutions
• Security & Compliance: Data tokenization techniques; compliance-aware architecture patterns; secure inference protocols; audit logging implementation
• BU Success Engineering: Technical documentation frameworks; knowledge transfer methodologies; executive-level technical demonstrations; BU/Function capability assessment
Preferred:
• Master's preferred.
• Full-stack dev experience on modern stack
• Modelling User Interactions with AI Systems; Modeling multi-agent behaviour loops with tools like Temporal
• Agentic memory Patterns and usage with tools like MEM0 and Temporal
• Experience with Agentic RAG; Domain level Semantic Layer Designs with Graph and Vector DBs
Company:
PepsiCo is a food and beverage company. Founded in 1898, the company is headquartered in Purchase, USA, with a team of 10001+ employees. The company is currently Late Stage.