agentic ai engineer

[JOB TITLE]

Agentic AI Engineer Python, Vertex AI(Gemini) LangChain, LangGraph, ADK,

[TECH STACK]

PRIMARY:

- Python

- LangChain

- LangGraph

- Vertex AI

- Embedding Models

-Prompt Engineering

- Evaluation Models

-RAG

SECONDARY:

- Vector Databases (FAISS, Pinecone)

- LLM APIs (GCP)

- Docker & CI/CD basics

EXCLUDE:

- Pure front-end roles

- Traditional ML Ops without GenAI work

[REQUIREMENTS]

- 2 years of experience in AI engineering with strong Python expertise.

- Hands-on experience building agentic or tool-using AI systems.

- Strong understanding of Vertex AI (Gemini), LangGraph and model fine-tuning workflows.

- Experience with LangChain for agent/tool orchestration.

- Knowledge of vector embeddings, retrieval pipelines, and LLM integration.

- Knowledge of GCP (BigQuery, GCS)

[EVALUATION TOPICS]

Topic

Weight

Type (Mandatory / Preferred)

Python & Systems Design

30%

Mandatory

GCP Vertex AI, Prompt Eng

25%

Mandatory

LangChain & Agent Design

25%

Mandatory

Retrieval, Vector DBs

10%

Preferred

Deployment & Optimization

10%

Preferred

[INTERVIEW FOCUS]

[HIGH]

- Python depth (async, multiprocessing, performance)

- Vertex AI (Gemini), Embedding Models, Prompt Engineering, Evaluation Models

- Building agentic workflows and tool-calling logic

[MEDIUM]

- Vector search design

- Prompt engineering for agent behavior

- Deployment/static analysis of model behavior

MUST:

- Ability to design and debug agent loops

- GCP Vertex AI

- Strong understanding of LLM constraints and safety

AVOID:

- Candidates with only academic ML experience

- People without hands-on GenAI pipeline work

-People without hands-on Agentic