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Innodatainc
Agentic AI Engineer
engineeringfull-timeRemote - United States
SALARY
$100k – $120k/yr
WORK TYPE
remote
JOB TYPE
full-time
INDUSTRY
ai
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About the role
Scope of the Role
We are seeking an Agentic AI Engineer to design, build, and deploy sophisticated multi-agent AI systems that operate autonomously across complex enterprise environments. You will architect agent-to-agent orchestration pipelines, fine-tune foundation models, and integrate retrieval-augmented generation (RAG) into scalable backend infrastructure — bridging the gap between cutting-edge AI research and real-world production deployment. This is a high-impact role at the frontier of agentic AI, building the intelligent systems that will define the next generation of enterprise automation.
What You’ll Own
- Design and implement multi-agent systems using LangChain, LangGraph, CrewAI, AutoGen or similar frameworks.
- Build A2A (agent-to-agent) orchestration and implement MCP (multi-context protocol) for context reuse and collaboration.
- Fine-tune foundation models (LoRA, RLHF, DPO) and integrate retrieval-augmented generation (RAG) pipelines.
- Develop APIs and backend services (FastAPI/Flask/Node.js) and integrate with enterprise systems (HRIS, CRM, ERP).
- Build secure data pipelines (ETL, embeddings, vector DB ingestion) and ensure governance, bias mitigation, and lineage.
- Containerize, deploy, and monitor agents (Docker, Kubernetes, CI/CD pipelines) with observability and drift detection.
- Collaborate with QA, red teaming, and product leads to benchmark accuracy, safety, and compliance.
You’ll Thrive in This Role If You Have
- Advanced proficiency in Python, PyTorch/TensorFlow, Hugging Face, and fine-tuning techniques (LoRA, RLHF).
- Hands-on experience with LangChain/LangGraph, MCP, A2A orchestration, and multi-agent architectures.
- Proficient in ETL pipelines, SQL/NoSQL, vector DBs (Pinecone, Weaviate, FAISS, Milvus).
- Backend expertise in FastAPI/Flask/Node.js, REST/GraphQL APIs, and microservices.
- DevOps/MLOps experience: Docker, Kubernetes, CI/CD (Jenkins/GitHub Actions), monitoring/observability.
- Cloud experience with AWS/GCP/Azure AI services and secure integration practices.
- Bonus: familiarity with enterprise HR/ATS systems (Workday, SAP, Paychex) and workflow automation.
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