AI Engineer

Role: AI Engineer (Gemini Enterprise)

Location: India (Remote)

About the Practice

Techolution operates as a forward-deployed engineering firm rather than a standard systems integrator. We build production-grade AI systems directly inside our clients' stacks at Google Cloud Premier Partner scale. This role sits within our AI Engineering practice, requiring you to embed with a client from day one and act as the primary technical point of contact for their AI team.

Key Responsibilities

• Architecture & Development: Architect and build multi-agent AI systems using Google Agent Development Kit (ADK) integrated with Gemini Enterprise on GCP. Design native connectors between Gemini Enterprise and enterprise platforms.
• Technical Leadership: Lead design reviews, architecture sign-offs, and sprint deliverables for non-technical stakeholders. Translate ambiguous business problems into engineered production AI architectures.

• Optimization & Reliability: Optimize agent performance, manage token budgets, implement grounding/retrieval pipelines, and ensure system reliability in production environments.

• Mentorship & Standards: Contribute to internal engineering standards, reusable frameworks, and maintain quality under delivery pressure. Perform code reviews and mentor junior engineers on client engagements.

What You Must Bring

• Google ADK Mastery: Hands-on experience building production agents with the Google Agent Development Kit (ADK). Proficiency in agent lifecycle management, tool registration, memory handling, and multi-agent orchestration without needing documentation.

• Gemini Enterprise Experience: Direct implementation experience with Gemini Enterprise or Gemini for Google Workspace APIs in a corporate environment. Focus on production workloads with real users, not experimental sandboxes.

• GCP Expertise: Working knowledge of Vertex AI, Cloud Run, Cloud Functions, BigQuery, Pub/Sub, and IAM. You must be able to deploy directly on GCP.

• Python Engineering: Strong skills in production-quality code with testing, error handling, observability (FastAPI, asyncio, LangChain or equivalents).

• Agent Architecture Fundamentals: Deep understanding of design patterns including ReAct, plan-and-execute, multi-agent delegation, tool-use with structured output, and context management.

• System Design & Communication: Sufficient CS fundamentals to architect scalable systems. Ability to present technical architecture to C-level stakeholders and defend design decisions under scrutiny is non-negotiable for this forward-deployed role.

Advantage Factors

• GCP Certifications (Professional Cloud Architect or Professional ML Engineer).

• Prior consulting experience where you were the named technical lead.

• Familiarity with Dialogflow CX, CCAI, RAG pipelines, vector databases, and enterprise document grounding.