Senior AI / GCP Technical Consultant – Agentic AI

Centraprise, Corp.; Bogotá ciudad; On-site; COP 120,000,000 - 240,000,000; Full time

Job summary

Centraprise, Corp. is seeking a Senior AI / GCP Technical Consultant to design and implement enterprise-grade AI and cloud solutions on Google Cloud Platform (GCP).

The role focuses on agentic AI, Generative AI, and scalable architectures, requiring hands-on GCP experience and collaboration with enterprise customers. Responsibilities include leading technical discovery, co-development with customer teams, and delivering production-ready AI/ML pipelines.

Qualifications

• Hands-on experience with Google Cloud Platform (GCP).
• Expertise in agentic and Generative AI.
• Experience with LangGraph, CrewAI, or ADK.
• Strong MVP-to-production delivery of AI/cloud solutions.
• 5+ years serving enterprise customers in technical consulting.

Responsibilities

• Work directly with enterprise customers to understand business challenges and transformation objectives.
• Lead technical discovery sessions and translate requirements into scalable solutions.
• Collaborate closely with customer engineering teams through hands-on co-development.
• Establish engineering best practices and reusable reference architectures.
• Provide technical guidance and support critical architecture decisions.
• Drive solutions from MVPs through production-grade implementations.

Skills

GCP hands-on

Agentic AI

Generative AI

Cloud architecture

Enterprise consulting

MCP / A2A patterns

AI security / guardrails

Stakeholder communication

SQL / NoSQL databases

Java / Go / C++ (plus)

Tools

LangGraph

CrewAI

ADK

Langfuse

AgentOps

Vertex AI

BigQuery

GKE

Cloud Run

REST APIs / gRPC / SSE

VPC Service Controls

Job description

Senior AI / GCP Technical Consultant – Agentic AI

We are seeking a highly experienced Senior AI / GCP Technical Consultant with strong hands-on experience designing and implementing enterprise-grade AI and cloud solutions on Google Cloud Platform (GCP).

Position Overview

The ideal candidate will have a strong background in Agentic AI, Generative AI, machine learning, cloud architecture, RAG, LLMOps, and enterprise consulting, along with the ability to work directly with engineering and business stakeholders to develop scalable, secure, and production-ready solutions.

Previous hands-on experience working with GCP is mandatory.

Key Responsibilities

Enterprise Consulting & Technical Leadership

• Work directly with enterprise customers to understand business challenges, technical requirements, and transformation objectives.
• Lead technical discovery sessions and translate business requirements into scalable technical solutions.
• Collaborate closely with customer engineering teams through hands-on co-development.
• Establish engineering best practices, develop reference implementations, and define reusable reference architectures.
• Provide technical guidance and support critical architecture and technology decisions.
• Drive solutions from initial concepts and MVPs through production-grade implementations.
• Identify technical risks, dependencies, and constraints within complex enterprise environments.
• Communicate technical concepts effectively to both technical and business stakeholders.
• Facilitate discussions around technical trade-offs and recommend appropriate solutions.

Agentic AI & Generative AI

• Design and implement enterprise-grade agentic AI architectures and workflows.
• Develop solutions using agent orchestration frameworks such as LangGraph, CrewAI, and Agent Development Kit (ADK).
• Implement agent architectures using Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication.
• Develop tool/function calling, dynamic routing, reasoning, self-reflection, and hierarchical delegation patterns.
• Design intelligent workflows that integrate multiple agents, tools, APIs, and enterprise systems.
• Build reusable AI components and modules that can be leveraged across multiple solutions.

RAG, Search & Data

• Design and implement Retrieval-Augmented Generation (RAG) solutions for enterprise use cases.
• Work with agent search, agent retrieval, vector databases, and enterprise knowledge systems.
• Hands-on experience with Cloud SQL, AlloyDB, BigQuery, and other modern data platforms.
• Design scalable data pipelines and backend data workflows supporting AI and ML applications.
• Work across SQL and NoSQL ecosystems to select appropriate data storage solutions.

Security & AI Guardrails

• Design and implement security controls for enterprise AI applications.
• Implement guardrails and semantic security mechanisms to mitigate:
• Jailbreak attempts
• PII and sensitive-data leakage
• Unsafe or invalid outputs
• Hallucinations
• Experience with solutions such as Model Armor is highly desirable.
• Implement enterprise-grade IAM, isolation, governance, and security controls.

LLMOps & Observability

• Implement observability and monitoring for AI and agentic workflows.
• Hands-on experience with tools such as Langfuse and AgentOps.
• Monitor and analyze agent workflows, A2A interactions, and LLM performance.
• Track key metrics including latency, token usage, cost, throughput, and model performance.
• Establish monitoring and continuous improvement processes for production AI systems.
• Design and manage end-to-end machine learning lifecycles.
• Hands-on experience with Vertex AI and managed GCP ML services.
• Experience with:
• AutoML
• Develop reliable and scalable ML/AI solutions from experimentation through production.
• Build AI and cloud solutions using:
• GKE
• BigQuery
• Firestore
• Develop integrations using REST APIs, gRPC, SSE, and other enterprise integration patterns.
• Implement secure architectures using VPC Service Controls (VPC-SC) and IAM.
• Work within strict enterprise security policies, governance requirements, and legacy technology environments.

Required Technical Skills

• Mandatory: Hands-on professional experience with Google Cloud Platform (GCP).
• Strong experience in Agentic AI and Generative AI.
• Experience with LangGraph, CrewAI, or ADK.
• Strong understanding of MCP, A2A, tool/function calling, dynamic routing, and agent reasoning patterns.
• Hands-on experience building RAG and retrieval-based AI solutions.
• Experience with Vertex AI and GCP ML/MLOps services.
• Strong knowledge of AI security, guardrails, semantic security, and responsible AI practices.
• Experience with Langfuse, AgentOps, or comparable observability platforms.
• Strong knowledge of SQL and NoSQL databases.
• Experience with BigQuery, Cloud Spanner, Cloud Bigtable, Firestore, Cloud SQL, and/or AlloyDB.
• Experience designing scalable data pipelines and backend systems.
• Experience with GKE, Cloud Run, Apigee, REST, gRPC, and SSE.
• Strong understanding of IAM, VPC Service Controls, enterprise security, and cloud governance.
• Additional programming experience with Java, Go, or C++ is a plus.

Professional Experience

• 5+ years of experience working directly with enterprise customers in technical consulting or solution architecture roles.
• Proven experience leading technical discovery and architecture discussions.
• Demonstrated experience with hands-on co-development alongside customer engineering teams.
• Experience delivering AI/cloud solutions from MVP through production.
• Strong ability to work within complex enterprise environments involving security, governance, legacy systems, and organizational constraints.
• Excellent communication, presentation, stakeholder management, and technical negotiation skills.