AI Engineer

Tech Mahindra; Pune District; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Tech Mahindra in Pune is seeking a Developer to build AI powered operational intelligence and automation on Google Cloud Platform. The role requires hands-on cloud engineering, data engineering, AI/ML, APIs, automation and AIOps tooling.

You will implement cloud native AIOps apps with Python, Vertex AI, Dataflow and BigQuery, develop telemetry pipelines, observability solutions, and MLOps pipelines, targeting production readiness and scalable microservices.

Qualifications

• Strong hands on development experience with Python.
• Experience with Google Cloud services including Vertex AI, BigQuery, Dataflow, Pub/Sub, GKE and Cloud Run.
• Experience developing APIs, microservices and cloud native applications.
• Hands on experience with machine learning and MLOps implementations.
• Experience building data ingestion, ETL and streaming data pipelines.
• Knowledge of Generative AI, LLMs, Gemini and Agentic AI frameworks.
• Experience with Kubernetes, Docker and container-based deployments.
• Familiarity with observability platforms including Datadog, Dynatrace, Splunk, Elastic or New Relic.
• Knowledge of ServiceNow integration and ITSM processes.
• Experience with GitHub, CI/CD automation and DevOps practices.
• Experience with Terraform and Infrastructure as Code.
• Strong troubleshooting, analytical and operational problem solving skills.

Responsibilities

• Develop cloud native AIOps applications using Python and Google Cloud services.
• Build operational intelligence solutions using Vertex AI to perform anomaly detection, prediction and operational analytics.
• Develop telemetry ingestion and processing pipelines using Pub/Sub, Dataflow and BigQuery.
• Build observability solutions that analyse logs, metrics and traces collected through Cloud Monitoring and OpenTelemetry.
• Develop event correlation and root cause analysis engines that improve incident management and operational efficiency.
• Build scalable microservices and REST APIs deployed on GKE, Cloud Run and serverless GCP platforms.
• Develop automation and self healing workflows that integrate with ServiceNow and enterprise IT operations platforms.
• Create AI powered operational assistants and Agentic AI workflows using Gemini and Vertex AI services.
• Develop data models, feature engineering pipelines and machine learning workflows supporting operational analytics use cases.
• Build and maintain MLOps pipelines using Vertex AI Pipelines for training, deployment and monitoring of AI models.
• Design CI/CD pipelines using GitHub Actions, Cloud Build and Kubernetes delivery frameworks.
• Implement Infrastructure as Code using Terraform to automate provisioning of cloud resources.
• Develop operational dashboards and KPI reporting solutions using BigQuery and Looker.
• Monitor solution performance, model drift, operational effectiveness and cloud resource utilisation.
• Collaborate closely with architects, platform engineers, SRE teams and business stakeholders to deliver production ready solutions.

Skills

Python

Google Cloud

APIs & microservices

ML & MLOps

ETL & data pipelines

Generative AI & LLMs

CI/CD & DevOps

Troubleshooting & problem solving

Tools

Kubernetes

Docker

Datadog

Dynatrace

Splunk

Elastic

New Relic

Terraform

GitHub Actions

Cloud Build

Looker

BigQuery

ServiceNow

Job description

A Bachelor’s or Higher Degree is the minimum entry required for the position

Role Summary

The Developer will develop AI powered operational intelligence, observability and automation solutions on Google Cloud Platform. The role requires strong hands on development expertise across cloud engineering, data engineering, AI/ML, APIs, automation and AIOps tooling.

Key Responsibilities

• Develop cloud native AIOps applications using Python and Google Cloud services.
• Build operational intelligence solutions using Vertex AI to perform anomaly detection, prediction and operational analytics.
• Develop telemetry ingestion and processing pipelines using Pub/Sub, Dataflow and BigQuery.
• Build observability solutions that analyse logs, metrics and traces collected through Cloud Monitoring and OpenTelemetry.
• Develop event correlation and root cause analysis engines that improve incident management and operational efficiency.
• Build scalable microservices and REST APIs deployed on GKE, Cloud Run and serverless GCP platforms.
• Develop automation and self healing workflows that integrate with ServiceNow and enterprise IT operations platforms.
• Create AI powered operational assistants and Agentic AI workflows using Gemini and Vertex AI services.
• Develop data models, feature engineering pipelines and machine learning workflows supporting operational analytics use cases.
• Build and maintain MLOps pipelines using Vertex AI Pipelines for training, deployment and monitoring of AI models.
• Design CI/CD pipelines using GitHub Actions, Cloud Build and Kubernetes delivery frameworks.
• Implement Infrastructure as Code using Terraform to automate provisioning of cloud resources.
• Develop operational dashboards and KPI reporting solutions using BigQuery and Looker.
• Monitor solution performance, model drift, operational effectiveness and cloud resource utilisation.
• Collaborate closely with architects, platform engineers, SRE teams and business stakeholders to deliver production ready solutions.

Required Skills

• Strong hands on development experience using Python.
• Good experience with Google Cloud services including Vertex AI, BigQuery, Dataflow, Pub/Sub, GKE and Cloud Run.
• Experience developing APIs, microservices and cloud native applications.
• Hands on experience with machine learning and MLOps implementations.
• Experience building data ingestion, ETL and streaming data pipelines.
• Knowledge of Generative AI, LLMs, Gemini and Agentic AI frameworks.
• Experience with Kubernetes, Docker and container based deployments.
• Familiarity with observability platforms including Datadog, Dynatrace, Splunk, Elastic or New Relic.
• Knowledge of ServiceNow integration and ITSM processes.
• Experience with GitHub, CI/CD automation and DevOps practices.
• Experience with Terraform and Infrastructure as Code.
• Strong troubleshooting, analytical and operational problem solving skills.