Experience
1 - 5 yrs
Job Location
Central Remote, Remote
Vacancy
1
Designation
Artificial Intelligence Engineer
Job Type
ONSITE
Job Description
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
Strong 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
No Referrers Available
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