GCP Agentic AI Developers - C2

Capgemini; Nashville (TN); On-site; USD 51,000 - 80,000; Full time

Benefits offered by this job

Remote-friendly project

Job summary

Tundra Technical Solutions is seeking a Staff Agentic AI Engineer to lead the design and delivery of enterprise-grade Generative AI on Google Cloud Platform, with Vertex AI at the core. You will architect RAG systems, embeddings, grounding, and autonomous agent architectures while mentoring engineers and promoting Agile delivery.

Responsibilities include building scalable cloud-native AI workloads, integrating LLMs with external tools, and establishing CI/CD and MLOps practices.

Qualifications

• Bachelor's degree is required.
• 8+ years of software development or engineering experience.
• Proven delivery of Generative AI solutions in enterprise or customer-facing environments.

Responsibilities

• Design, build, and deploy scalable Generative AI solutions on GCP using Vertex AI.
• Architect and implement RAG systems, including data ingestion, embeddings, vector search, and retrieval pipelines.
• Design grounding and embedding strategies to improve response accuracy and factuality.
• Develop Agentic AI and multi-agent systems for autonomous task execution.
• Integrate LLMs with external tools, services, and enterprise systems using structured interaction patterns (e.g., MCP).
• Build and manage cloud-native, containerized, and serverless AI workloads.
• Establish CI/CD pipelines and MLOps practices for AI/ML systems.
• Collaborate with product, business, and engineering stakeholders to translate requirements into AI solutions.
• Lead technical design reviews, investigations, PoCs, and solution proposals.
• Mentor engineers and promote best practices in AI engineering and Agile delivery.

Skills

Problem solving

Technical leadership

Communication

Mentoring

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Vertex AI

Dataflow

Dataproc

Pub/Sub

Kafka

Docker

Kubernetes

Job description

GCP Agentic AI Developers - C2 (Contract)

Contract (3 months 15 days)

Published 2 days ago

SQL/NoSQL database

mlops

Problem - Solving Skills

DevOps & CI/CD

LLM Integration

GCP Cloud

The Staff Agentic AI Engineer leads the design and delivery of enterprise-grade Generative AI and Agentic AI solutions on Google Cloud Platform (GCP), with a primary focus on Vertex AI. This role emphasizes production-ready AI systems, including Retrieval-Augmented Generation (RAG), grounding, embeddings, and autonomous agent architectures, while providing technical leadership and mentorship.

Key Responsibilities:

Design, build, and deploy scalable Generative AI solutions on GCP using Vertex AI.

Architect and implement RAG systems, including data ingestion, embeddings, vector search, and retrieval pipelines.

Design grounding and embedding strategies to improve response accuracy and factuality.

Develop Agentic AI and multi-agent systems for autonomous task execution.

Integrate LLMs with external tools, services, and enterprise systems using structured interaction patterns (e.g., MCP).

Build and manage cloud-native, containerized, and serverless AI workloads.

Establish CI/CD pipelines and MLOps practices for AI/ML systems.

Collaborate with product, business, and engineering stakeholders to translate requirements into AI solutions.

Lead technical design reviews, investigations, PoCs, and solution proposals.

Mentor engineers and promote best practices in AI engineering and Agile delivery.

Required Skills & Experience:

Hands-on experience with Vertex AI and generative models (e.g., Gemini).

Strong experience designing and delivering RAG architectures in production.

Experience with vector databases, embeddings, and data grounding techniques.

Proficiency in Python and at least one of: Java, C#, or Node.js.

Experience with SQL and NoSQL databases (e.g., SQL Server, Cosmos DB, MongoDB).

Experience with data pipelines and messaging systems (e.g., Dataflow, Dataproc, Pub/Sub, Kafka).

Strong background in cloud-native architectures, Docker, Kubernetes, and microservices.

Experience with DevOps and CI/CD for ML/MLOps.

Strong communication, problem-solving, and technical leadership skills.

Preferred Qualifications:

Experience with Agentic AI frameworks (e.g., LangChain).

Familiarity with Model Context Protocol (MCP) or similar LLM tool-integration approaches.

Experience integrating AI solutions with CRM, ERP, eCommerce, or EMR/EHR systems.

Education:

Bachelor's degree in Computer Science, Engineering, or related field.

8+ years of software development or engineering experience.

Proven delivery of Generative AI solutions in enterprise or customer-facing environments.

The pay range that the employer in good faith reasonably expects to pay for this position is $36.98/hour - $57.79/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.

Tundra Technical Solutions is among North America's leading providers of Staffing and Consulting Services. Our success and our clients' success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.