Senior AI Ops Architect

EPAM Systems; Maharashtra; On-site; INR 3,500,000 - 6,000,000; Full time

Benefits offered by this job

AIOps leadership experience

AWS ML certs

Job summary

EPAM Systems is seeking a Senior AI Ops Architect with 10+ years in enterprise IT and a strong focus on Gen-AI-enabled platforms, observability, and automation. You will architect, implement, and lead Gen-AI/LMM engineering efforts across AWS, Azure, GCP, and on-prem environments, driving MTTR reduction and operational excellence.

The role requires deep experience in MLOps, data-driven automation, and enterprise-grade AIOps solutions, with a strong command of English and demonstrated leadership

Qualifications

• 10+ years of enterprise cloud, infrastructure, SRE, automation and architecture experience.
• Proven Gen-AI powered AIOps production deployments
• Experience with large-scale enterprise platforms and ITSM integrations
• Strong knowledge of MLOps, SageMaker, Azure ML, and Vertex AI
• Hands-on experience with cloud-native, serverless architectures
• Familiarity with observability tools and data-driven operational intelligence
• Effective written and spoken English (B2 level or higher)

Responsibilities

• Design Gen-AI-powered AIOps solutions for large enterprises to reduce MTTR and automate incidents
• Architect Gen-AI & LLM engineering using Bedrock, OpenAI, Vertex AI, Anthropic, and LangChain
• Develop and optimize MLOps pipelines and deployment workflows
• Implement RAG, Vector DBs, and semantic search across platforms
• Build cloud platforms and infra using AWS, Azure, GCP, Terraform, CloudFormation, Helm
• Lead Kubernetes-based infra, CI/CD, Istio, and KEDA deployment strategies
• Design serverless and cloud-native architectures using API Gateway, Lambda, Step Functions, DynamoDB, S3, Kinesis
• Implement end-to-end Observability with DataDog, OpenTelemetry, Dynatrace, New Relic, Splunk, Moogsoft, BigPanda
• Ensure ITSM integration with ServiceNow, Jira Service Management, Manage Engine
• Provide thought leadership in AIOps and AI-powered operational intelligence

Skills

Executive leadership

English communication

Tools

Amazon Bedrock

Azure OpenAI

Vertex AI

LangChain

SageMaker

Azure ML

PGVector

Elasticsearch

DataDog

OpenTelemetry

Dynatrace

New Relic

Splunk

Moogsoft

BigPanda

ServiceNow

Jira Service Management

Manage Engine

Kubernetes

CI/CD

Istio

KEDA

API Gateway

Lambda

Step Functions

DynamoDB

S3

Kinesis

Terraform

CloudFormation

Helm

Python

Shell Scripting

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