Overview

Job DescriptionJob DescriptionJob Title: Artificial Intelligence Senior Associate Location: Dearborn, MI (local preferred)Duration: 12 Months (with potential for extension)Interview: Interview onsite in South Lyon/Novi, MI Candidate must be USC or GC. Do not apply for C2C. It will be a hybrid position. REVIEW JD MAKE SURE REQUIRED SKILLS (highlighted red) ARE ON THE RESUME. Will be onsite 4 days a week.Position Description: Employees in this job function are responsible for developing intelligent programs, cognitive applications and algorithms for data analysis and automation, leveraging various AI techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programmingKey Responsibilities:Understand business requirements and develop AI algorithms, models and programs to solve complex problems, generate recommendations, extract patterns, make predictions, interpret sensor data (images, sound), orchestrate automation and enable self-service capabilitiesPerform large-scale experimentation and develop data driven applications that translate data into actionable intelligenceDrive innovative applications of Artificial Intelligence tools and techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programmingResearch and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more efficient automationSkills Required:Google Cloud PlatformExperience Required:Bachelor's or Master's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience).3+ years building production software systems, including 1-2+ years on ML/AI or LLM-based applications. Proven experience designing and deploying multi-agent or multi-service architectures in production - not just notebooks or demos.As one 2026 hiring analysis puts it, the job is closer to distributed systems engineering with a probabilistic component than it is to ML research or prompt tweaking .Strong Python proficiency, including async/concurrent programming, and experience with backend frameworks (FastAPI, Flask).Hands-on experience with agent orchestration frameworks - LangGraph, CrewAI, LlamaIndex, or equivalent - for building stateful, multi-step, tool-using agent workflows.Practical experience building RAG pipelines: vector databases (pgvector, Pinecone, Weaviate, or Qdrant), embeddings, chunking strategies, and retrieval evaluation. Cloud deployment experience, ideally Google Cloud Platform (BigQuery, Cloud Run/GKE, Vertex AI, Pub/Sub) or equivalent AWS/Azure services.Strong SQL skills and experience with cloud data warehouses. Containerization and CI/CD experience (Docker, Kubernetes, GitHub Actions/Cloud Build).Experience building evaluation and observability pipelines for LLM/agent systems - offline eval sets, LLM-as-judge scoring, and tracing tools (LangSmith, Langfuse, OpenTelemetry, or equivalent) to track task success, latency, and cost.Understanding of LLM safety practices: guardrails, output validation, prompt-injection defense, and safe execution of AI-generated code/SQL (sandboxing, least privilege). Solid software engineering fundamentals: API design, testing, version control, security best practices.Experience Preferred:Experience with cost optimization and model routing - designing tiered pipelines that route between low-cost and high-capability models based on task complexity, and modeling per-conversation or per-task cost at scale.Experience deploying agentic systems with human-in-the-loop or multi-checkpoint validation workflows for high-reliability/high-stakes use cases.Experience with automotive, EV charging, IoT, or connected-vehicle telemetry data.Familiarity with Model Context Protocol (MCP) or simil