Agentic AI Engineer - Machine Learning

Job Description : Agentic AI Engineer

We are seeking a highly skilled Agentic AI Engineer with a robust background in Data Engineering and Machine Learning to join our team on a permanent, full-time basis. This role is pivotal in bridging the gap between ambiguous business requirements and deterministic, high-performance AI agent tools.

The ideal candidate will have 6-8+ years of experience and a proven track record of deploying scalable AI applications, specifically utilizing the Claude LLM ecosystem and advanced data modeling.

Role : Agentic AI Engineer

Experience : 5-8 Years (6-8+ preferred in Data/ML)

Location : Chennai, Bangalore, Hyderabad, Pune

Notice Period : Immediate Joiner to 15 days (Strict)

Interview Process : 2 Comprehensive Technical Rounds

Key Responsibilities :

- Agentic Framework Development : Design and implement AI agents using Claude LLM (Anthropic API/Amazon Bedrock) focusing on tool-use, structured outputs, and complex reasoning chains.

- RAG & Vector Search : Build and optimize Retrieval-Augmented Generation (RAG) pipelines using Azure Cognitive Search or pgvector.

- Backend Engineering : Develop high-performance APIs using FastAPI/Flask, incorporating asynchronous patterns and rigorous testing (pytest).

- Data & Analytics Engineering : Leverage DAX and Power Query (M) for time intelligence and performance patterns; manage Tabular operations via XMLA.

- Deployment & Ops : Manage the full lifecycle of AI applications via Azure Functions/App Service and maintain CI/CD pipelines through GitHub Actions or Azure DevOps.

Mandatory Skills & Qualifications :

1. Agentic AI & Machine Learning :

- Practical experience with Claude LLM (Anthropic/Bedrock).

- Expertise in Structured Outputs and Tool-use/Function Calling.

- Deep understanding of RAG design and vector database implementation.

2. Python & Backend Development :

- Expert-level Python (AsyncIO, Logging, Packaging).

- Experience with FastAPI or Flask.

- Solid grasp of security, compliance, and observability in production environments.

3. Data Engineering & Analytics :

- Proficiency in DAX (Performance patterns, XMLA).

- Advanced Power Query (M) skills.

- Experience in Data/Analytics Engineering or ML application architecture.

(ref:hirist.tech)