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Tekonika - Agentic AI Engineer - LLM

Tekonika Technologies
5 - 10 Years
Bangalore

Posted on: 30/03/2026

Job Description

Description :


We are looking for a senior-level Agentic AI Architect to define and lead the design of enterprise-grade autonomous AI systems.

This role focuses on architecture, scalability, governance, and long-term AI strategy, rather than hands-on framework-level implementation.

You will work closely with leadership, product, and engineering teams to build robust AI platforms that power intelligent automation across the organization.

Key Responsibilities :

AI Strategy & Architecture :


- Define the overall architecture for agentic AI platforms and autonomous systems

- Design scalable, secure, and production-grade AI ecosystems

- Drive adoption of agent-based architectures across business units

System Design & Governance :


- Establish standards for AI system design, model usage, and deployment

- Define guardrails for responsible AI (bias, hallucination control, explainability)

- Implement governance frameworks including auditability and compliance

Platform & Infrastructure Leadership :

- Architect enterprise AI platforms integrating LLMs, APIs, and distributed systems

- Lead decisions on infrastructure, cloud architecture, and scalability patterns

- Drive performance optimization, cost management, and reliability

Cross-functional Leadership :


- Partner with business leaders to identify AI transformation opportunities

- Translate business vision into scalable AI solutions

- Mentor engineering teams and define best practices

Innovation & Thought Leadership :


- Stay ahead of advancements in AI, multi-agent systems, and autonomous workflows

- Drive innovation initiatives and POCs at an organizational level

Required Skills & Qualifications :


- 5 - 10 years of experience in AI/ML, Data Engineering, or Backend Architecture

- Strong experience in system design and distributed architectures

- Experience designing enterprise-scale AI platforms

- Deep understanding of LLM capabilities and limitations

- Strong experience with cloud platforms (AWS/Azure/GCP)

- Expertise in APIs, microservices, and scalable backend systems


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