Note: The job is a remote job and is open to candidates in USA. Panasonic Automotive develops technology and engineering solutions for automotive experiences, including infotainment and connected vehicle systems. The Senior AI Full Stack Engineer will design, build, and ship production-grade AI-powered applications across the full stack, integrating LLMs, RAG pipelines, agentic systems, responsive interfaces, backend services, and cloud infrastructure. The role supports AI-driven features for connected vehicles, in-vehicle infotainment, manufacturing intelligence, and enterprise tools.
Responsibilities
- Design and build end-to-end AI-powered product features — owning the full stack from React/Next.js UI through FastAPI/Node.js backend services to cloud infrastructure and LLM integrations
- Architect and implement LLM integration layers: connecting to OpenAI, Anthropic Claude, Google Gemini, Meta Llama, or other foundation models via APIs, fine-tuned endpoints, or on-device inference
- Build production-grade RAG (Retrieval-Augmented Generation) pipelines: document ingestion, chunking strategies, embedding generation, vector store management, and orchestrated retrieval for accurate, low-hallucination AI responses
- Develop multi-agent and agentic workflow systems using frameworks such as LangChain, LangGraph, CrewAI, or AutoGen — designing agent memory, tool use, planning loops, and goal decomposition
- Engineer prompt engineering strategies, guardrails, and context management systems that optimize LLM output for latency, cost, and quality at scale
- Build and maintain scalable microservices and event-driven backend architectures (Kafka, Redis, async queues) to handle high-throughput AI workloads and long-running agent tasks
- Design responsive, performant front-end experiences that elegantly surface AI capabilities — including real-time streaming responses (WebSocket/SSE), conversational UIs, AI-assisted dashboards, and multi-modal interfaces
- Establish observability and monitoring frameworks for AI production systems: model performance tracking, hallucination detection, token cost monitoring, latency profiling, and bias alerting
- Implement responsible AI controls at the application layer: input/output guardrails, content filtering, PII redaction, rate limiting, and audit logging for regulatory compliance
- Integrate AI features into automotive-domain applications including connected vehicle dashboards, IVI systems, manufacturing quality intelligence platforms, and supply chain optimization tools
- Collaborate with AI Architects to translate architecture blueprints into production code; provide engineering feedback that improves architectural decisions
- Champion engineering excellence: code reviews, automated testing (unit, integration, AI evaluation), CI/CD pipelines, and documentation for AI-enabled features
Skills
- 7+ years of professional full stack engineering experience with at least 2+ years building and shipping production AI/LLM-integrated features
- Proven track record delivering AI-powered products to real users at scale — prototypes do not count
- Expert-level proficiency in React and Next.js (App Router, SSR, SSG, streaming); TypeScript required
- Experience building real-time AI interfaces: streaming LLM responses via WebSocket or
- Server-Sent Events (SSE), conversational chat UIs, and multi-modal content displays
- Trong command of modern CSS, state management (Zustand, Redux Toolkit, or Jotai), and UI component libraries
- Solid understanding of microservices design patterns: event-driven architecture, message queues (Kafka, Redis Pub/Sub, Celery/Taskiq), and fault-tolerant distributed systems
- Database proficiency: PostgreSQL, MongoDB, and Redis for caching and session management
- Hands-on production experience integrating LLM APIs: OpenAI GPT-4o, Anthropic Claude, Google Gemini, Meta Llama, or Mistral
- Deep expertise in RAG architecture: document processing, embedding models, chunking strategies, semantic search, vector databases (Pinecone, Weaviate, Chroma, pgvector, Qdrant)
- Experience with agentic AI frameworks: LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or OpenAI Agents SDK
- Strong prompt engineering and context engineering skills; experience designing multi-turn conversations, tool-calling workflows, and structured LLM output parsing
- Experience implementing LLM guardrails, hallucination mitigation, and output validation for production systems
- Strong experience with at least one major cloud platform: AWS, Azure, or GCP; familiarity with managed AI/ML services (AWS Bedrock, Azure OpenAI Service, Vertex AI)
- Containerization and orchestration: Docker and Kubernetes; experience with Helm charts and cloud-native deployments
- CI/CD pipelines for AI-enabled products: automated testing, model evaluation gates, and zero-downtime deployments
- AI observability tooling: LangSmith, Weights & Biases, Helicone, or Arize for LLM tracing, cost tracking, and quality monitoring
- General observability: OpenTelemetry, Prometheus, Grafana, or Datadog for distributed tracing, metrics, and alerting
- All candidates must have valid authorization to work in the U.S
- Bachelor's degree in Computer Science, Software Engineering, or related technical field; Master's degree a plus
- Strong Python backend development using FastAPI (preferred) or equivalent; experience building async, high-throughput REST and streaming APIs
Benefits
- 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
Company Overview