Agentic AI Engineer

Overview

We are seeking a highly skilled

Agentic AI Engineer

to design, develop, and deploy autonomous AI agents and workflows within the

Google Cloud Platform (GCP)

ecosystem. The ideal candidate will have hands-on expertise in building multi-agent AI systems, integrating LLMs (such as Gemini, GPT, or Claude), and orchestrating intelligent pipelines that leverage GCP services for scalability, observability, and security. This role requires a deep understanding of

AI architecture, vector search, orchestration frameworks, and event-driven cloud systems . You will collaborate with data engineers, MLOps teams, and solution architects to deliver real-world AI capabilities that adapt, reason, and act autonomously.

Key Responsibilities

Agentic AI & LLM Integration

Design and implement

autonomous AI agents

capable of reasoning, planning, and executing workflows using LLMs (Gemini, GPT, Claude, etc.).

Implement multi-agent coordination frameworks (e.g., LangChain, CrewAI, AutoGen, or Semantic Kernel).

Build adaptive memory systems and contextual knowledge retrieval pipelines using

Vertex AI ,

BigQuery , and

GCP Vector Search .

Integrate with external APIs and enterprise systems using secure, event-driven architectures.

Develop and deploy AI workloads in

GCP

leveraging:

Vertex AI ,

Pub/Sub ,

Cloud Run ,

Cloud Functions , and

BigQuery .

GCS

for storage and

Cloud Composer (Airflow)

for orchestration.

Build

containerized microservices

(Docker / Kubernetes / GKE) for scalable AI workflows.

Implement CI/CD pipelines using

Cloud Build

or

GitHub Actions

for rapid iteration.

Architect retrieval-augmented generation (RAG) pipelines using

GCP Vector Search ,

Pinecone , or

Weaviate .

Connect unstructured and structured data sources to LLMs using

Dataform ,

BigQuery , and

Vertex AI Matching Engine .

Design prompt optimization, context management, and long-term memory storage strategies.

Security, Governance, and Observability

Enforce IAM, service accounts, and least-privilege policies across agent workflows.

Integrate

Cloud Logging ,

Cloud Monitoring , and

Dynatrace

(if applicable) for full observability of agent actions.

Implement data governance and compliance standards for AI model usage and external API calls.

Partner with product, ML, and software teams to define use cases for agentic automation.

Continuously evaluate emerging frameworks for multi-agent systems and adaptive reasoning.

Contribute to architectural roadmaps, PoCs, and AI innovation initiatives within the organization.

Qualifications

Bachelor’s or Master’s degree

in Computer Science, Data Science, or related field.

5+ years of experience in cloud-based development (GCP preferred).

3+ years of experience with

LLM-based applications

(LangChain, LlamaIndex, or OpenAI APIs).

Strong programming skills in

Python, Go, or Node.js .

Experience with

RAG ,

vector databases , and

agent orchestration frameworks .

Familiarity with

Vertex AI ,

GKE ,

Pub/Sub ,

BigQuery , and

Cloud Functions .

Solid understanding of

MLOps ,

microservices , and

event-driven design .

Preferred Skills

Experience with

Google Gemini API

or other advanced foundation models.

Knowledge of

Autonomous AI frameworks

(e.g., AutoGPT, BabyAGI, CrewAI).

Exposure to

LangGraph

or

Semantic Kernel

for graph-based agent design.

Experience integrating

AI observability tools

(Weights & Biases, Arize AI, or Vertex AI Model Monitoring).

Understanding of

RAG governance , compliance, and cost optimization strategies.

Employment details

Seniority level: Mid-Senior level

Employment type: Full-time

Job function: Information Technology

Industries: IT Services and IT Consulting

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