01
TRCD-26-05243
Software Engineer – AI Platform (Agentic AI)
Software Engineer to design and deliver an enterprise agentic AI platform on AWS, building AI agents and agentic workflows, MCP (Model Context Protocol) servers/tool integrations, and scalable backend services/APIs plus full-stack features for AI-enabled applications. The role emphasizes AI engineering best practices (RAG/vector search, prompt/context management, evaluation/testing, guardrails/security/responsible AI, observability/monitoring, multi-agent orchestration) and strong distributed systems design, working in agile teams with modern CI/CD.
Position summary
- Location
- India
- Workplace
- On-site
- Employment
- Contract
- Experience
- Minimum 5 years and Maximum 8 years
Role overview
Why This Role Matters.
Software Engineer to design and deliver an enterprise agentic AI platform on AWS, building AI agents and agentic workflows, MCP (Model Context Protocol) servers/tool integrations, and scalable backend services/APIs plus full-stack features for AI-enabled applications. The role emphasizes AI engineering best practices (RAG/vector search, prompt/context management, evaluation/testing, guardrails/security/responsible AI, observability/monitoring, multi-agent orchestration) and strong distributed systems design, working in agile teams with modern CI/CD.
Your Impact
Deliver Enterprise Value
Help organisations solve complex business problems through modern technology, consulting expertise and measurable outcomes.
Collaboration
Work Across Teams
Collaborate with consultants, architects, engineers and client stakeholders throughout the project lifecycle.
Growth
Learn Continuously
Gain exposure to enterprise technologies, certifications, mentoring and real-world project experience.
Career Path
Grow With Ubique
Build a long-term consulting career with opportunities to take on greater responsibility and leadership over time.
Responsibilities
What You'll Be Doing.
Every role at Ubique contributes directly to solving meaningful business challenges for our clients.
02
Build AI agents and agentic workflows that automate and augment business processes
03
Develop MCP (Model Context Protocol) servers and tool integrations that connect agents to enterprise systems, APIs, and data
04
Integrate the AI platform with AWS services and existing enterprise applications
05
Build backend services and APIs, and develop full-stack features and user interfaces for AI-enabled applications
06
Apply AI engineering best practices to ensure the quality, security, reliability, and performance of agentic solutions
07
Create reusable AI components, services, and architectural patterns for use across engineering teams
08
Partner with engineering teams and business stakeholders to identify and deliver AI enablement opportunities
09
Participate in agile delivery using modern CI/CD practices
10
This helps scale AI enablement by building reusable agentic capabilities, shared AI services, and integrations that improve efficiency across the enterprise.
11
Improved enterprise efficiency through AI-driven automation of manual and repetitive business processes
12
Faster adoption of AI capabilities across business functions and applications
Technology stack
Tools & Technologies.
The platforms and technologies you'll use to build modern, enterprise-grade solutions.
01
AWS
Required
02
Agentic AI
Required
03
AI agents
Required
04
LLM
Required
05
RAG
Required
06
vector search
Required
07
knowledge base
Required
08
prompt engineering
Required
09
context management
Required
10
agent evaluation
Required
11
agent testing
Required
12
guardrails
Required
13
responsible AI
Required
14
AI security
Required
15
observability
Required
16
monitoring
Required
17
multi-agent orchestration
Required
18
MCP
Required
19
Model Context Protocol
Required
20
tool integrations
Required
Requirements
Skills & Experience.
We value curiosity, collaboration and continuous learning. If you don't meet every requirement but believe you can make an impact, we'd still love to hear from you.
Essential
Required Qualifications
5+ years software engineering experience
AWS cloud development (building, deploying, scaling cloud-native solutions)
Design and development of enterprise agentic AI platforms
Building AI agents / LLM-powered applications using agent development frameworks
RAG / knowledge bases and vector search
Prompt engineering and context management
Agent evaluation and testing
Guardrails, security, and responsible AI practices
Agent observability and monitoring
Multi-agent orchestration
Building MCP (Model Context Protocol) servers and tool integrations
Backend services and API development
Scalable distributed systems design (low latency, high throughput, reliability, performance)
Architecture and technical design across multiple systems/teams
Agile delivery with modern CI/CD practices
Proficiency in one or more: Python, Next.js, React, Node.js, TypeScript, Java, Kotlin (or similar)
Preferred
Nice to Have
Amazon Bedrock
Amazon Bedrock AgentCore
Platform modernization experience
Large-scale engineering initiatives across multiple teams
What you'll gain
More Than Just A Job.
We're committed to helping every team member grow professionally, personally and technically while working on meaningful projects.
Global Exposure
Collaborate with international clients and multicultural teams on enterprise programmes.
Continuous Learning
Expand your expertise through mentoring, certifications and hands-on project experience.
Career Growth
Take ownership, develop leadership skills and grow your consulting career over time.
Flexible Working
Hybrid and remote collaboration designed around trust and delivering exceptional outcomes.
People First
Join a supportive culture where collaboration, respect and long-term relationships come first.
Enterprise Projects
Work on meaningful technology initiatives for leading organisations across industries.
Apply
Apply for Software Engineer – AI Platform (Agentic AI)
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