Senior Agentic AI Platform Engineer – MCP & Agent Runtime

ITOrizon; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

A global consulting and technology company seeks a Senior Agentic AI Platform Engineer in Bengaluru, Karnataka. In this role, you will build the core AI agent platform infrastructure including runtimes and SDKs. The ideal candidate has strong engineering experience and deep Python expertise. This position involves designing machine learning models and collaborating with engineering teams to ensure scalable solutions. Join a cutting-edge AI-first platform and tackle enterprise challenges in multi-tenancy, security, and observability.

Qualifications

• 5+ years of strong engineering experience with production system ownership.
• Deep expertise in Python and AI platform development.
• Experience building scalable, reusable platform components.

Responsibilities

• Design, develop, and deploy machine learning models for enterprise use cases.
• Collaborate with engineering teams to productionize models.
• Ensure model performance, scalability, explainability, and reliability.

Skills

Python

Machine Learning

MLOps Practices

Data Analysis

Deep Learning

Job 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

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