Senior AI Ops Architect

EPAM Systems; Bengaluru; On-site; INR 4,200,000 - 7,000,000; Full time

Job summary

EPAM Systems in Bengaluru seeks a Senior AI Ops Architect to drive Gen-AI-enabled cloud engineering, observability, and automation at enterprise scale. You will design scalable AIOps platforms, build AI-driven automation, and advance operational efficiency across complex environments.

The role requires 10+ years in enterprise architecture, strong MLOps and cloud experience (AWS/Azure/GCP), Kubernetes, and ITSM integrations, with excellent English communication.

Qualifications

• 19+ years of overall IT experience
• 10+ years in Enterprise Cloud, Infrastructure, SRE, Automation and Architecture roles
• Proven Gen-AI-powered AIOps deployments in production
• Experience with Bedrock, OpenAI, Vertex AI, Anthropic, LangChain
• Proficiency in RAG, Vector DBs, semantic search (PGVector, Elasticsearch)
• MLOps with SageMaker, Azure ML, clustering, topic modeling, anomaly detection
• Cloud engineering with AWS, Azure, GCP, Terraform, CloudFormation, Helm
• Kubernetes-based infrastructure, CI/CD, Istio, KEDA
• Serverless/cloud-native: API Gateway, Lambda, Step Functions
• Observability tools: DataDog, OpenTelemetry, Dynatrace, New Relic, Splunk, Moogsoft, BigPanda
• ITSM platforms: ServiceNow, Jira Service Management, Manage Engine
• English communication (B2+)

Responsibilities

• Design Gen-AI-powered AIOps for large enterprise platforms to reduce MTTR
• Architect Gen-AI & LLM solutions using Bedrock, OpenAI, Vertex AI
• Develop and optimize MLOps pipelines and deployment workflows
• Implement RAG, vector DBs and semantic search
• Automate Cloud Platforms with AWS, Azure, GCP, Terraform
• Lead Kubernetes-based orchestration and DevSecOps, CI/CD, Istio, KEDA
• Design serverless and cloud-native architectures (API Gateway, Lambda)
• Implement end-to-end Observability with DataDog, OpenTelemetry, Dynatrace, New Relic, Splunk, Moogsoft, BigPanda
• ITSM integration for AI-driven operations
• Work with ServiceNow, Jira Service Management, ManageEngine
• Provide thought leadership in AIOps and automation

Skills

Gen-AI engineering

LLM engineering

SRE & automation

Kubernetes

CI/CD

Observability

Security automation

Python

Shell scripting

Terraform

Tools

Amazon Bedrock

Azure OpenAI

Vertex AI

LangChain

Bedrock Agents

SageMaker

OpenTelemetry

DataDog

Dynatrace

New Relic

Splunk

Moogsoft

BigPanda

Terraform

CloudFormation

Helm

API Gateway

Lambda

DynamoDB

S3

Kinesis

Elasticsearch

PGVector

Jira Service Management

ServiceNow

ManageEngine

Job description

We are seeking a highly experienced Senior AI Ops Architect with exceptional expertise in Gen-AI-enabled Cloud Engineering, Observability, Operational Intelligence, and AI-driven automation. The ideal candidate will bring 10+ years of enterprise-level architecture experience, with a focus on building innovative Gen-AI-enabled platforms, data-driven automation frameworks, and enterprise-grade AIOps solutions to advance operational efficiency.

Responsibilities

• Design and deliver scalable Gen-AI-powered AIOps solutions for large enterprise platforms to improve MTTR, achieve automated incident resolution, and drive operational excellence
• Architect and implement Gen-AI & LLM Engineering solutions using tools such as Amazon Bedrock, Azure OpenAI, Vertex AI, Anthropic, and LangChain
• Develop and optimize MLOps pipelines and model deployment workflows leveraging SageMaker, Azure ML, clustering, topic modeling, and anomaly detection techniques
• Implement RAG, Vector DBs, and advanced semantic search across platforms using PGVector, Elasticsearch, and Bedrock Knowledge Sources
• Create and automate solutions for Cloud Platforms and Infrastructure with AWS, Azure, GCP, Terraform, CloudFormation, and Helm, alongside Python and Shell Scripting
• Lead Kubernetes-based container orchestration and DevSecOps initiatives, including CI/CD pipelines, Istio, and KEDA deployment strategies
• Design and integrate serverless and cloud-native architectures using API Gateway, Lambda, Step Functions, DynamoDB, S3, and Kinesis
• Implement end-to-end Observability solutions using DataDog, OpenTelemetry, Dynatrace, New Relic, Splunk, Moogsoft, and BigPanda
• Ensure seamless ITSM and ServiceNow integration for AI-driven operations and automation
• Work with ITSM tools like ServiceNow, Jira Service Management, and Manage Engine to streamline incident management workflows
• Provide thought leadership in AIOps, automation, and AI-powered operational intelligence to leadership and engineering teams

Requirements

• 19+ years of overall IT experience
• 10+ years of professional experience in Enterprise Cloud, Infrastructure Engineering, SRE, Automation, and Architecture roles
• Proven track record of delivering Gen-AI-powered AIOps solutions in production environments, driving efficiencies like MTTR improvement and operational automation
• Expertise in Gen-AI and LLM Engineering tools such as Amazon Bedrock, Azure OpenAI, Vertex AI, Anthropic, LangChain, and Bedrock Agents
• Proficiency in RAG, Vector Databases, and semantic search solutions like PGVector, Elasticsearch, and Bedrock Knowledge Sources
• Background in MLOps, model development, and machine learning techniques using SageMaker, Azure ML, clustering, topic modeling, and anomaly detection
• Skills in cloud engineering and automation technologies, including AWS, Azure, GCP, Terraform, CloudFormation, Helm, Python, and Shell Scripting
• Capability to design and operate Kubernetes-based infrastructure, CI/CD pipelines, security automation, Istio, and KEDA
• Familiarity with serverless computing and cloud-native tools like API Gateway, Lambda, Step Functions, DynamoDB, S3, and Kinesis
• Knowledge of Observability platforms such as DataDog, OpenTelemetry, Dynatrace, New Relic, Splunk, Moogsoft, and BigPanda
• Understanding of ITSM platforms, including ServiceNow, Jira Service Management, and Manage Engine
• Showcase of AI and Machine Learning expertise in areas like anomaly detection, GenAI implementation, and agentic AI solutions
• Ability to communicate effectively in both written and spoken English (B2 level or higher)

Nice to have

• Experience leading AIOps/Cloud Practices or platform engineering organizations
• Certifications in AWS ML, Cloud Architecture, or AI Leadership