Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale.

We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. 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. 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).

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. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process.

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