What are the responsibilities and job description for the Artificial Intelligence Senior Associate position at Up2date Technologies?
Role: Artificial Intelligence Senior Associate
Location: Dearborn, MI (Hybrid)
Contract Type: Fulltime
Overview / Summary:
We are seeking an Artificial Intelligence Senior Associate to develop and deploy production-grade AI applications, algorithms, and intelligent automation solutions. This role focuses on building multi-agent systems, RAG pipelines, data-driven applications, and AI services that solve complex problems, generate recommendations, extract patterns, make predictions, and enable self-service capabilities.
The role involves working across generative AI, natural language processing, deep learning, cognitive automation, intelligent process automation, and related AI technologies, with a strong emphasis on production software engineering, scalability, safety, evaluation, and observability.
Required Qualifications:
Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.
3 years of experience building production software systems, including 1–2 years working on ML/AI or LLM-based applications.
Proven experience designing and deploying multi-agent or multi-service architectures in production.
Strong Python proficiency, including asynchronoconcurrent programming.
Experience with backend frameworks such as FastAPI or Flask.
Hands-on experience with agent orchestration frameworks such as LangGraph, CrewAI, LlamaIndex, or equivalent.
Experience building RAG pipelines, including vector databases, embeddings, chunking strategies, and retrieval evaluation.
Cloud deployment experience, ideally with Google Cloud Platform.
Experience with cloud technologies such as BigQuery, Cloud Run/GKE, Vertex AI, and Pub/Sub, or equivalent AWS/Azure services.
Strong SQL skills and experience with cloud data warehouses.
Experience with containerization and CI/CD, including Docker, Kubernetes, and GitHub Actions/Cloud Build.
Experience building evaluation and observability pipelines for LLM/agent systems, including offline evaluation datasets, LLM-as-judge scoring, and tracing tools such as LangSmith, Langfuse, OpenTelemetry, or equivalent.
Understanding of LLM safety practices, including guardrails, output validation, prompt-injection defense, and safe execution of AI-generated code or SQL.
Strong software engineering fundamentals, including API design, testing, version control, and security best practices.
Experience with Google Cloud Platform.
Preferred Qualifications:
Experience with cost optimization and model routing, including tiered pipelines and per-task or per-conversation cost modeling.
Experience deploying agentic systems with human-in-the-loop or multi-checkpoint validation workflows.
Experience with automotive, EV charging, IoT, or connected-vehicle telemetry data.
Familiarity with Model Context Protocol (MCP) or similar standards for tool and data integration across agents.
Experience in a startup or 0-to-1 product environment with evolving requirements.
Master's degree in Computer Science, Software Engineering, or a related field.