We are looking for a highly skilled Agentic AI / Generative AI Engineer to design, build, and deploy intelligent autonomous workflows for enterprise-scale use cases. The role will focus on leveraging agentic frameworks, LLM orchestration, and workflow automation tools to solve complex business problems, particularly in regulated and data-intensive environments.

The ideal candidate should have strong experience in workflow automation (n8n), multi-agent frameworks like CrewAI, and cloud-native AI architectures across AWS/Azure.

Key Responsibilities

Design and implement agent-based AI systems using frameworks like CrewAI, LangGraph, or similar.

Develop and manage workflow automation pipelines using n8n (on-premise deployment).

Build multi-step reasoning workflows integrating LLMs, APIs, databases, and enterprise systems.

Develop end-to-end GenAI solutions, including prompt engineering, RAG pipelines, and tool usage.

Integrate AI agents with enterprise data sources (databases, APIs, document repositories).

Deploy and manage scalable solutions on AWS and/or Azure.

Ensure security, compliance, and governance, especially for sensitive enterprise data.

Optimize performance, latency, and cost of LLM-based workflows.

Collaborate with business stakeholders to translate requirements into AI-driven solutions.

Mandatory Skills

Agentic AI & Workflow Automation





Hands-on experience with CrewAI, LangChain Agents, or similar agent frameworks like AutoGen, LangGraph, Semantic Kernel

Robust expertise in n8n (especially on-premise setup and workflow orchestration)

Experience building autonomous decision-making workflows

Programming & AI Development

Strong proficiency in Python

Experience with LLM APIs (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI)

Knowledge of prompt engineering and RAG (Retrieval-Augmented Generation)

Knowledge of vector databases (Pinecone, FAISS, OpenSearch, Weaviate)

Cloud & Infrastructure

Experience with AWS and/or Azure

AWS: Bedrock, Lambda, S3, ECS/EKS

Azure: OpenAI, Functions, Blob Storage

Other Skills

Experience with event-driven architectures

Understanding of CI/CD pipelines for AI applications

Understanding of containerization (Docker, Kubernetes)

Familiarity with observability tools (LangSmith, Prometheus, Grafana)

Knowledge of data engineering pipelines (ETL/ELT)

Strong analytical and problem-solving mindset

Ability to identify errors and inconsistencies in data/models

Experience working with large enterprise customers

Understanding of regulated environments (Life Sciences, Pharma)

Ability to design secure, compliant AI workflows

Strong stakeholder communication skills

📌 Agentic AI and GenAI Engineer (Karnataka)
🏢 Sparix Global
📍 Karnataka