karnataka senior agentic ai platform engineer – mcp & agent runtime Jobs – 13 Open Jobs Today

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Senior Agentic AI Platform Engineer – MCP & Agent Runtime
ITOrizon —Bengaluru, Karnataka
This is a coding-first, platform-focused role—you will not build isolated AI use cases, but instead create reusable systems, developer tooling, and scalable…
Senior Platform Engineer: Agentic AI - Cogentiq
Fractal Analytics —Bengaluru, Karnataka
As a Senior Platform Engineer – Agentic AI, you will play a critical role in integrating, deploying, and scaling Cogentiq, Fractal’s enterprise-grade agentic AI…

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Senior Agentic AI Platform Engineer – MCP & Agent Runtime

ITOrizon -
Bengaluru, Karnataka

Apply Now

Job details

Full-time

Qualifications

CI/CD
Azure
Oracle
Go
Node.js
Law
MCP
Kubernetes
Enterprise Software
CISSP
CCSP
Java
Master's degree
Databases
Microservices
RBAC
AWS
Docker
Machine learning
Continuous integration
SDKs
Azure Certification
Natural language processing
APIs
AI
Python
Design patterns

Full job description

Position title

Senior Agentic AI Platform Engineer – MCP & Agent Runtime

Description

About Us

ITOrizon is a global consulting and technology company that helps enterprises design, implement, and optimize complex supply chain and digital transformation initiatives. Headquartered in Atlanta, USA, with offices in India (Bengaluru) and the UAE (Sharjah), we partner with global clients across retail, manufacturing, logistics, and distribution sectors.

We combine deep domain expertise with modern technology to deliver practical, scalable solutions. Our teams work across strategy, implementation, and managed services — helping organizations adopt leading platforms such as Oracle, Manhattan, Blue Yonder, and our next-generation composable enterprise platform, Karolium.

Role Overview

We are looking for a Senior Agentic AI Platform Engineer to build the core platform infrastructure for AI agents, including runtimes, SDKs, MCP integrations, and evaluation frameworks.

This is a coding-first, platform-focused role—you will not build isolated AI use cases, but instead create reusable systems, developer tooling, and scalable infrastructure that enable teams to build and operate AI agents reliably across the enterprise.

Key Responsibilities

Design, develop, and deploy machine learning and statistical models for enterprise use cases
Perform data exploration, feature engineering, and model evaluation on structured and unstructured data
Build predictive, prescriptive, and descriptive analytics solutions
Work with large-scale datasets, real-time data pipelines, and cloud data platforms
Collaborate with engineering teams to productionize models using MLOps practices
Develop and optimize models across:
- Classical ML (regression, classification, clustering)
- Time-series forecasting & anomaly detection
- Deep learning & NLP
Ensure model performance, scalability, explainability, and reliability
Implement model monitoring, versioning, and lifecycle management
Contribute to AI architecture, experimentation frameworks, and innovation initiatives
Stay updated with AI/ML and GenAI advancements and apply them to real-world problems

Agent Runtime & Platform Foundations

Build and maintain a scalable Agent Runtime with:
- Orchestration primitives
- Tool routing, retries, fallbacks
- Memory and state management
- Guardrails and safety controls
Design reusable agent execution frameworks for multi-tenant environments

Developer Platform & SDKs

Develop a developer-first Agent SDK including:
- Libraries, templates, and reference implementations
Standardize how internal teams build, deploy, and manage AI agents

MCP (Model Context Protocol) & Integrations

Implement MCP exposure layers for secure tool access
Build MCP servers and connectors for:
- Enterprise systems
- Internal platform services
Ensure authentication, authorization, and auditability

RAG & Knowledge Systems

Design and implement platform-grade RAG pipelines, including:
- Data ingestion and chunking strategies
- Embedding pipelines and vector databases
- Retrieval, reranking, and grounding mechanisms

Evaluation, Observability & Reliability

Build evaluation frameworks:
- Offline evaluation
- Prompt/tool regression testing
- Quality metrics and drift detection
Implement observability systems:
- Tracing, logging, telemetry
- Cost/token optimization
- Latency and error monitoring

Enterprise Platform Readiness

Ensure multi-tenancy and platform security, including:
- Tenant isolation
- Environment separation (Dev/QA/Prod)
- Secret management
- Role-based access control (RBAC)
Integrate with enterprise systems:
- APIs, integration frameworks, security layers

Engineering Excellence

Drive clean code practices, design patterns, and architecture standards
Conduct code reviews and technical documentation
Contribute to platform roadmap and innovation initiatives

Required Skills & Expertise

Core Engineering (Coding-First)

Strong hands-on expertise in Python (primary language)
Experience with Java / Node.js / Go (multi-language ecosystem)
Strong fundamentals in:
- API design
- Clean architecture & design patterns
- Performance optimization
Experience building:
- Microservices
- Secure APIs
- Integration platforms

Agentic AI & LLM Engineering

Experience building tool-using AI agents, including:
- Function/tool calling
- Prompt engineering & templates
- Conversation state & memory
- Guardrails and structured outputs
Understanding of MCP concepts and implementations

RAG & Data Systems

Hands-on experience with:
- Vector databases & embeddings
- Retrieval strategies and ranking
- Grounding and citation technique

Cloud & Platform Engineering

Experience with AWS and/or Azure
Familiarity with:
- Docker & Kubernetes
- CI/CD pipelines
- Enterprise security and networking

Preferred Certifications

AWS Certified Machine Learning – Specialty
Microsoft Certified: Azure AI Engineer / Data Scientist
Kubernetes (CKA / CKAD)
Security certifications (CISSP, CCSP)

Good-to-Have Skills

Experience building internal developer platforms (IDPs) or SDKs
Familiarity with:
- Multi-agent systems
- Orchestrator/supervisor patterns
Knowledge of Responsible AI, governance, and audit frameworks

Ideal Candidate Profile

5+ years of strong engineering experience with production system ownership
Deep expertise in Python and AI platform development
Experience building scalable, reusable platform components
Strong platform mindset (enabling teams, not just solving use cases)
High adaptability in rapidly evolving AI ecosystems

Why Join Us?

Build core AI agent platform infrastructure (runtime, SDKs, MCP)
Work on enterprise-scale AI challenges:
- Multi-tenancy
- Security
- Observability
- Governance
Be part of a cutting-edge AI-first platform roadmap

How to Apply:

Email your Resume to [email protected]

Hiring organization

Employment Type

Full-time

Experience

5+ Years

Role Category

Agentic AI Engineer

Role

Senior

Job Location

Bangalore, India, India

Date posted

April 9, 2026

Apply Now

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