AI Engineer- Remote position

Role & responsibilities

The resource will design, develop, and productionize AI agents that automate complex enterprise/engineering workflows (Windchill process automation - Mostly). The agents should be capable of retrieving information from databases, APIs and documents; reasoning over that information; performing validations; invoking tools/APIs; and either taking an action or routing exceptions for human review.

This is not primarily a Data Scientist, chatbot developer, or RAG PoC role. The ideal candidate is a strong Python/AI engineer who has delivered at least two GenAI or Agentic AI solutions, understands agent orchestration, and can take a solution from PoC

PrioritySearch CategoryKeywords

Must HaveAgentic AI: Agentic AI, AI Agents, Autonomous Agents, Multi-Agent Systems, Agent Orchestration

Must HaveAgent Frameworks: LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel

Must Have Development Python, FastAPI, REST API, Microservices

GenAI / LLMGenerative AI, LLM, GPT, Claude, Llama, Mistral, Open-Source LLM

HighRAGRAG, Retrieval Augmented Generation, LlamaIndex, Vector Database, Hybrid Search

Agent CapabilitiesTool Calling, Function Calling, Memory, Planning, State Management, Human-in-the-Loop

ProductionProduction GenAI, LLMOps, MLOps, Docker, Kubernetes, CI/CD

EvaluationLLM Evaluation, RAGAS, DeepEval, LangSmith, Hallucination Evaluation

ObservabilityAgent Tracing, LLM Monitoring, OpenTelemetry, Logging, Audit Trail

Data IntegrationSQL, NL-to-SQL, API Integration, Document Processing, Structured/Unstructured Data

OptimizationQuantization, Model Pruning, vLLM, ONNX, TensorRT-LLM, Semantic Caching, Model Routing

CloudAzure OpenAI, Azure AI, AWS Bedrock, SageMaker, GCP Vertex AI

AdvantageAI/MLNLP, Computer Vision, Deep Learning, PyTorch, TensorFlow

Advantage Enterprise AIMCP, GraphRAG, Knowledge Graph, Guardrails, Responsible AI