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Ai Full Stack Jobs (NOW HIRING)

AI Full Stack Developer

Portland, OR · On-site

$125K - $165K/yr

Internal AI tool delivery -- Design, build, and maintain a suite of internal tools on Retool -- from initial prototype to production deployment. Own the full stack: Retool application, Python backend ...

Full Stack Engineer

San Francisco, CA · On-site

$150 - $200/hr

Design and integrate LLMs and other AI models into our applications, including data collection ... Full-stack or AI projects and internships * Interest in HVAC, plumbing, or other field-service ...

Full Stack Engineer (AI-focused) Location: Remote Job Summary: We are seeking a highly skilled and motivated Full Stack Engineer to join our dynamic team. The ideal candidate will have a strong ...

Full Stack Engineer (AI-focused) Location: Remote Job Summary: We are seeking a highly skilled and motivated Full Stack Engineer to join our dynamic team. The ideal candidate will have a strong ...

... AI or LLM-based applications that real users depend on. * Genuine full-stack depth: modern TypeScript/React or equivalent on the front end, Python or TypeScript services on the back end, relational ...

... building AI or LLM-based applications that real users depend on. Genuine full-stack depth: modern TypeScript/React or equivalent on the front end, Python or TypeScript services on the back end, ...

$125 - $150/hr

... building AI or LLM-based applications that real users depend on. Genuine full-stack depth: modern TypeScript/React or equivalent on the front end, Python or TypeScript services on the back end, ...

We're hiring a senior full-stack engineer to build the product experiences and AI systems at the core of WorkHero-from React and React Native workflows to Node services, tool-using agents, and human ...

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Ai Full Stack information

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How much do ai full stack jobs pay per year?

As of Sep 9, 2026, the average yearly pay for ai full stack in the United States is $134,771.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $158,000.00 per year, depending on experience, location, and employer.

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Infographic showing various Ai Full Stack job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution, with an average salary of $134,771 per year, or $64.8 per hour.

Senior AI Full Stack Engineer

Farmington Hills, MI • On-site

Panasonic Automotive
Electrical Equipment, Appliance, and Component Manufacturing • 1 - 5K employees

$125 - $150/hr

Other

Medical, Dental, Retirement

Posted 8 days ago


Key responsibilities

  • Design, build, and ship production‑grade AI‑powered applications across full stack from UI to cloud infrastructure.

  • Architect and implement LLM integration layers, including connecting to various foundation models via APIs and on‑device inference.

  • Build and maintain scalable microservices and event‑driven backend architectures to handle high‑throughput AI workloads and long‑running agent tasks.


Job description

Overview

Senior AI Full Stack Engineer will design, build, and ship production‑grade AI‑powered applications that sit at the intersection of modern web engineering and the rapidly evolving world of generative AI and agentic systems.

We are looking for an engineer who is AI‑native: someone who instinctively reaches for LLM APIs, RAG pipelines, multi‑agent orchestration, and vector databases as core building blocks — while also owning the complete product surface from a performant React/Next.js front end through a scalable FastAPI or Node.js back end to cloud‑deployed, observable production systems.

You will partner with AI Architects, data scientists, product managers, and UX designers to deliver AI‑driven features across connected vehicle platforms, in‑vehicle infotainment (IVI), manufacturing intelligence, and internal enterprise tools — serving customers and users at scale.

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.
A DAY IN THE LIFE
  • Day‑to‑day work involves coding, debugging, testing, collaborating, and contributing to strategic design, while ensuring quality, performance, and safety throughout the product lifecycle.
MUST‑HAVES
  • Bachelor’s degree in Computer Science, Software Engineering, or related technical field; Master’s degree a plus.
  • 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.
  • Strong command of modern CSS, state management (Zustand, Redux Toolkit, or Jotai), and UI component libraries.
  • Strong Python backend development using FastAPI (preferred) or equivalent; experience building async, high‑throughput REST and streaming APIs.
  • 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.
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
  • Additional benefits and perks detailed in 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 (OEMs) 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 or without reasonable accommodations.

Job ID: REQ-152095

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