{"id":2774131,"url":"https://alion.io/job/tech-mahindra-gcp-developer","title":"GCP developer","company":{"id":5484,"name":"Tech Mahindra","domain":"techmahindra.com","url":"https://alion.io/company/tech-mahindra","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"CI/CD","optional":false},{"name":"Datadog","optional":false},{"name":"Docker","optional":false},{"name":"Dynatrace","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Gemini","optional":false},{"name":"GitHub","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google Cloud Run","optional":false},{"name":"Google GKE","optional":false},{"name":"Incident Management","optional":false},{"name":"ITSM","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Looker","optional":false},{"name":"Machine Learning","optional":false},{"name":"New Relic","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Self-Healing","optional":false},{"name":"ServiceNow","optional":false},{"name":"Splunk","optional":false},{"name":"Terraform","optional":false},{"name":"Vertex AI","optional":false}],"status":"live","first_seen_at":"2026-10-17T07:35:15Z","employer_posted_date":"2026-10-17","last_verified_at":"2026-10-25T13:55:43Z","board_verified":true,"closed_at":null,"days_open":8,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":8},"description":"Job Description\n\nSkill Set :\nPython,GCP,Vertex AI,Generative AI,LLM,AIOps,RAG\n\nTotal Experience :\n5.00 to 10.00 Years\n\nNo of Openings :\n1\n\nJob Post Date :\n12/08/2026\n\nJob Expiry Date :\n30/11/2026\n\nDomain :\nIT\n\nLocation :\nPUNE [India]\n\nJob Reference No :\n4101394\n\nJob Summary\nRole Summary\nThe 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.\nKey Responsibilities\n• Develop cloud native AIOps applications using Python and Google Cloud services.\n• Build operational intelligence solutions using Vertex AI to perform anomaly detection, prediction and operational analytics.\n• Develop telemetry ingestion and processing pipelines using Pub/Sub, Dataflow and BigQuery.\n• Build observability solutions that analyse logs, metrics and traces collected through Cloud Monitoring and OpenTelemetry.\n• Develop event correlation and root cause analysis engines that improve incident management and operational efficiency.\n• Build scalable microservices and REST APIs deployed on GKE, Cloud Run and serverless GCP platforms.\n• Develop automation and self healing workflows that integrate with ServiceNow and enterprise IT operations platforms.\n• Create AI powered operational assistants and Agentic AI workflows using Gemini and Vertex AI services.\n• Develop data models, feature engineering pipelines and machine learning workflows supporting operational analytics use cases.\n• Build and maintain MLOps pipelines using Vertex AI Pipelines for training, deployment and monitoring of AI models.\n• Design CI/CD pipelines using GitHub Actions, Cloud Build and Kubernetes delivery frameworks.\n• Implement Infrastructure as Code using Terraform to automate provisioning of cloud resources.\n• Develop operational dashboards and KPI reporting solutions using BigQuery and Looker.\n• Monitor solution performance, model drift, operational effectiveness and cloud resource utilisation.\n• Collaborate closely with architects, platform engineers, SRE teams and business stakeholders to deliver production ready solutions.\nRequired Skills\n• Strong hands on development experience using Python.\n• Good experience with Google Cloud services including Vertex AI, BigQuery, Dataflow, Pub/Sub, GKE and Cloud Run.\n• Experience developing APIs, microservices and cloud native applications.\n• Hands on experience with machine learning and MLOps implementations.\n• Experience building data ingestion, ETL and streaming data pipelines.\n• Knowledge of Generative AI, LLMs, Gemini and Agentic AI frameworks.\n• Experience with Kubernetes, Docker and container based deployments.\n• Familiarity with observability platforms including Datadog, Dynatrace, Splunk, Elastic or New Relic.\n• Knowledge of ServiceNow integration and ITSM processes.\n• Experience with GitHub, CI/CD automation and DevOps practices.\n• Experience with Terraform and Infrastructure as Code.\n• Strong troubleshooting, analytical and operational problem solving 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