AI Architect

Panasonic Automotive North America; Peachtree City (GA); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Great Medical/Dental Benefits

401K retirement savings match

Annual Bonus program

Educational Assistance

Relaxed Dress Code

Onsite Happy Hours

Job summary

Panasonic Automotive North America is seeking a hands-on AI Solution Architect to design and build production‑scale agentic AI systems. This individual contributor role focuses on writing code, delivering reference implementations, and taking designs from prototype to production.

You will partner with business and technical teams to deliver enterprise AI solutions across the organization. You will design multi‑agent architectures, build RAG pipelines, and ensure secure, compliant deployments

Qualifications

• 7+ years of software engineering experience with 2+ years delivering LLM or agent-based systems to production.
• Strong Python development and working knowledge of TypeScript or another backend language.
• Hands-on with LLM APIs, function calling, and structured outputs.
• Experience with vector/hybrid search and embeddings.
• Experience designing MCP and tool integrations; familiarity with agent standards.
• Experience building LLM evaluations and observability (OpenTelemetry, Langfuse, LangSmith).
• Cloud deployment experience on AWS, Azure, or GCP with Docker, Kubernetes and secure API design.
• Daily use of AI coding assistants and agents in engineering workflows.

Responsibilities

• Turn business use cases into end-to-end enterprise AI solutions with design and delivery roadmaps.
• Integrate AI with ERP, identity/SSO, data platforms, APIs and legacy apps.
• Design and build single- and multi-agent systems with orchestration and memory.
• Develop RAG pipelines, context engineering, and latency management.
• Build MCP servers and agent integrations exposing enterprise tools under least-privilege access.
• Route LLM access through a gateway with model routing, quotas, and cost tracking.
• Create evaluation, tracing, and monitoring for LLM/agent behavior and releases.
• Secure agents against prompt injection and data leakage; maintain audit trails.
• Deploy AI services with containers, CI/CD, and infrastructure as code.
• Support enterprise rollout: pilots, adoption, and handoff; share reference architectures.

Skills

LLM/agent shipping

Python

TypeScript

LLM APIs

Vector search

MCP/tool integration

Observability/OpenTelemetry

Cloud deployment (AWS/Azure/GCP)

Docker/Kubernetes

Requirements-to-production

Security/compliance

Tools

LangGraph

Semantic Kernel

LangSmith/Langfuse

OAuth/OIDC

Job description

Overview

Panasonic Automotive is looking for a hands‑on AI Solution Architect to design and build production agentic AI systems. This is an individual contributor role with no people management. You will write code, build reference implementations, and take designs from prototype to production. You will partner with business and technical teams across the organization to deliver AI solutions.

Overview

Panasonic Automotive is looking for a hands‑on AI Solution Architect to design and build production agentic AI systems. This is an individual contributor role with no people management. You will write code, build reference implementations, and take designs from prototype to production. You will partner with business and technical teams across the organization to deliver AI solutions.

Responsibilities

A DAY IN THE LIFE

• Work with business and technical stakeholders to turn use cases into end‑to‑end enterprise AI solutions: requirements, solution design, build‑versus‑buy and platform choices, and delivery roadmaps.
• Integrate AI with enterprise systems and data (ERP, identity and SSO, data platforms, APIs, and legacy applications) within existing architecture, security, and compliance standards.
• Design and build single‑and‑multi‑agent systems: orchestration, tool use, memory, and human‑in‑the‑loop controls.
• Build RAG and context‑engineering pipelines, including retrieval quality, long‑running agent memory, and token and latency management.
• Build MCP servers and agent integrations that expose enterprise tools and data under governed, least‑privilege access.
• Run LLM access through a gateway with model routing, fallback, quotas, and cost and usage tracking.
• Build evaluation, tracing, and monitoring for LLM and agent behavior, including regression tests and release gates.
• Secure agents against prompt injection, data leakage, and over‑permissioned tools; keep audit trails of agent actions.
• Deploy AI services with containers, CI/CD, and infrastructure as code, and troubleshoot them in production.
• Support rollout of AI solutions across the enterprise: pilots, user adoption, operational handoff, and feedback loops.
• Publish reference architectures and working templates, and review designs and code with partner teams.

Must‑haves

• 7+ years of software engineering experience, including 2+ years shipping LLM, RAG, or agent‑based systems to production.
• Strong Python; working knowledge of TypeScript or another backend language.
• Hands‑on with LLM APIs and open‑weight models, function calling, structured outputs, and agent frameworks (for example LangGraph, Semantic Kernel, or similar).
• Experience with vector or hybrid search and embeddings.
• Experience with MCP and tool‑integration design; familiarity with A2A or similar agent interoperability standards.
• Experience building LLM evaluations and observability (for example OpenTelemetry‑based tracing, Langfuse, or LangSmith).
• Cloud deployment experience on AWS, Azure, or GCP, with Docker, Kubernetes, and secure API design (OAuth/OIDC).
• Daily use of AI coding assistants and agents in your own engineering workflow.
• Experience delivering enterprise solutions: integrating with enterprise applications, SSO/identity, and data platforms under security and architecture review.
• Clear communication of design trade‑offs, in writing and in person.

Nice‑to‑have

• Model serving or fine‑tuning experience (for example vLLM, LoRA), including edge or on‑device inference.
• Working knowledge of AI governance frameworks (NIST AI RMF, ISO/IEC 42001, EU AI Act).
• Automotive, embedded, or manufacturing software background.
• Vendor‑neutral certifications or public technical work in AI systems.

Benefits & Perks - We're All About You

• Great Medical/Dental Benefits
• Company‑Matched 401K Retirement Savings
• Annual Bonus Program
• Educational Assistance
• Relaxed Dress Code
• PASATalks Speaker Summits
• Leadership & Mentorship Programs
• High5 Reward Recognition Program
• Onsite Happy Hours
• And many more benefits & perks found within the ‘Our Culture’ section…

Who We Are

At Panasonic, our technology and engineering expertise delivers innovation across diverse industries. It's all about the consumer experience and making sure that we find ways to enhance that experience, either through audio enhancements or through safety enhancements inside the vehicle. Panasonic Automotive Systems Company of America (PASA) is an industry‑leading global supplier to Automotive Original Equipment Manufacturers (OEM’s) for infotainment systems and advanced connected car solutions. Our clients include Ford, GM, Chrysler, Daimler, Fiat, Tesla, Honda, Toyota.

We Take Opportunity Seriously

Panasonic is an Equal Opportunity/Affirmative Action employer, and all qualified applicants will receive consideration for employment without regard to: race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, disability status, protected veteran status, or any other characteristics protected by law. All qualified individuals are required to perform the essential functions of the job with our without reasonable accommodations. Due to the high volume of responses, we will only be able to respond to candidates of interest. All candidates must have valid authorization to work in the U.S. Thank you for your interest in Panasonic Automotive Systems of America.

Job ID

REQ-152089