Job Description
As a
Agentspace AI Engineer , you will design, build, scale, and productionize agentic systems powered by Google's Gemini Enterprise platform—the unified, enterprise-grade front-door for AI agents, deep enterprise search, and multimodal reasoning.
You will transform business friction (fragmented data, slow research, manual workflows) into high-ROI autonomous agents that operate across
Google Workspace, Salesforce, SAP, and BigQuery , ensuring every deployment meets rigorous enterprise security and governance standards.
Job Title: Agentspace AI Engineer
Duration: Full-Time
Location: Hyderabad
Working hours : 2:00 PM IST to 11:00 PM IST
No of Openings: 2
Key Responsibilities:
Agent Orchestration:
work on custom multi-agent systems using
Gemini Enterprise, Vertex AI Agent Builder , and the
Agent Development Kit (ADK) .
Enterprise Grounding:
Build secure pipelines to integrate Gemini with internal data using
Vertex AI Search .
Scale RAG Architectures:
Design RAG systems that combine structured data and real-time APIs with multimodal content (docs, images, and spreadsheets).
Enablement:
Create reusable no-code agent templates within the
Gemini Enterprise Workbench
.
Production Guardrails:
Own the reliability and safety of agent workloads, including
function calling, PII redaction, and hallucination mitigation .
Governance:
Partner with Security teams to implement enterprise controls, including
IAM, VPC Service Controls (VPC-SC), and data residency .
Optimization:
Track and improve Agent ROI using metrics like
task completion rate, latency, and cost-per-inference .
Qualifications:
AI Engineering Depth:
2–3+ years specifically shipping
production-grade GenAI/LLM systems .
Google AI Stack:
Deep proficiency in
Vertex AI, Gemini 1.5/2.0+ (Pro & Flash) , and the
Vertex Agent Engine .
Agentic Patterns:
Proven experience with
ReAct, Chain-of-Thought, Tool-Use (Function Calling) , and stateful orchestration.
Core Technical Stack:
Advanced
Python
and experience with
Enterprise APIs (OAuth, REST, GraphQL) .
Data & Search:
Experience with
BigQuery , Vector Databases, and
Vertex AI Search & Conversation
Enterprise Security:
Familiarity with
Cloud KMS/CMEK ,
DLP API , and audit logging within a cloud environment.
Differentiators (Nice-to-Have)
Specific Platform Experience:
Prior deployments using
Gemini Enterprise
or
LangGraph
for hierarchical agent swarms.
Multimodal Expertise:
Experience building agents that process video, complex document layouts, or real-time audio.
About Techolution :
Techolution is the
world's #1 AI Acceleration Partner
and the inventor of
BPA 4.0 , the groundbreaking AI platform that delivers
guaranteed ROI from enterprise AI in 30 days or less .
With over 10+ years of experience, we specialize in turning AI into measurable business value—helping global enterprises achieve dramatic efficiency gains (like 42x improvements in key processes), modernize legacy systems, migrate to the cloud (as a Google Premier Partner), and deploy custom AI solutions across industries such as healthcare, manufacturing, media, banking, government, and life sciences.
Our mission is simple yet powerful:
"TURN AI INTO ROI"
— where it matters most. We go beyond generic AI by offering risk-free innovation, including our
100k Challenge
(2x quantifiable savings in 100 days or your money back), rapid diagnostics via
BPA Value Finder , and AI-powered managed services that deliver twice the quality at half the cost.
Backed by 12 patents, 5 notable awards (including Inc. 5000 recognition), 2 published books, and a track record of solving real-world challenges—from patient prioritization during COVID-19 to quality control in supply chains and air quality monitoring—we empower teams to thrive in an AI-driven future.
At Techolution, we're building "innovation done right" with a passionate, collaborative team focused on delivering next-level impact, workforce enablement, and trustworthy, enterprise-scale automation. Join us to be part of redefining how businesses operate with AI.
Visit us
@
www.techolution.com
:
To know more about our revolutionary core practices and getting to know in detail about how we enrich the human experience with technology.