Pipeline run

917dd5ca-f7bd-4f90-9ead-c2809e0b9b39

Pipeline LLM cost (USD)

API 1: $0.0051 API 2: $0.0000 API 3: $0.0000 Total: $0.0051

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description

Nature of work · Data Infrastructure & Engineering

Build and run cloud data/ML infrastructure: design time-series storage and ETL/ELT pipelines on AWS/Azure, wire up CI/CD and MLOps, and monitor/automate deployments while handling releases, Sev1 incidents, and RCA. Also build KPI/analytics tooling and drive process automation.

"Design and develop scalable solutions for storing and retrieving high-volume time-series data."

Tech stack maturity

Modern Cloud Native

The skill set centers on cloud platforms, Kubernetes, Terraform, CI/CD, observability, and modern data/ML tooling like Databricks, MLOps, and GitHub Actions, which is characteristic of a modern cloud-native stack.

AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)

1.70 / 5

· Title match

✓ Has AI skill

✓ AI skill (primary)

· AI skill (secondary)

· On AI team

· Builds AI products

vocab breakdown (legacy)

Assistants (×1): —

Frameworks (×2): —

Models / concepts (×3): MLOps, ML

Evidence — skills matched in JD (27)

AWS Azure Spark Kafka Kinesis Azure Data Factory MLflow Jenkins GitHub Actions Terraform Prometheus Grafana Databricks S3 Blob Storage SQL Python Java Scala Kubernetes CI/CD ETL ELT MLOps Ansible +2

Skill cluster (12 dimension groups, role-scoped)

CI/CD Pipeline Platforms

Jenkins GitHub Actions CI/CD

Cloud Platforms

AWS Azure S3

Infrastructure as Code

Terraform DevOps

Observability and Incident Triage

Prometheus Grafana

Asynchronous Messaging and Event Streaming

Kafka

CI/CD for Machine Learning

MLOps

Configuration Management

Ansible

Container Orchestration Platforms

Kubernetes

Java Language and JVM

Java

Programming Languages for ML Systems

Scala

Python Programming

Python

Cross-cutting / unaligned

Spark Kinesis Azure Data Factory MLflow Databricks Blob Storage SQL ETL ELT Time-series data

Show KRA description ↓

• Data Infrastructure & Engineering: Design and develop scalable solutions for storing and retrieving high-volume time-series data. Build robust ETL/ELT pipelines using AWS and Azure big data tools (e.g., Spark, Kafka, Kinesis, Azure Data Factory). • CI/CD & MLOps: Develop and manage CI/CD pipelines for ML models and data infrastructure using MLflow, Jenkins, GitHub Actions, and Terraform. Enable reproducible, secure, and scalable deployments. • Monitoring & Automation: Implement end-to-end monitoring for infrastructure, data pipelines, and ML services using Prometheus, Grafana, and custom alerting tools. Automate workflows to ensure high availability and zero-downtime deployments. • Release & Incident Management: Manage releases across staging and production environments. Respond to Severity 1 incidents, lead root cause analysis (RCA), and implement permanent fixes. • Collaboration & Process Improvement: Work with product teams to deploy releases, resolve customer escalations, and drive automation to improve onboarding and integration timelines. • Analytics Enablement: Build tools to deliver insights into customer acquisition, operational efficiency, and business KPIs. • Education & Certification: Bachelor’s or Master’s in Engineering with 4+ years in SRE or related roles. AWS Solution Architect Associate or Azure certification preferred. Familiarity with DevOps tools like Jenkins, Terraform, Ansible. • Technical Skills: Strong experience with cloud platforms (AWS, Azure), big data technologies (Spark, Kafka, Databricks), and data storage (S3, Blob Storage). Proficient in SQL, Python, Java/Scala, and container orchestration (Kubernetes preferred). • Soft Skills: Excellent communication, documentation, and time management. Strong problem-solving and customer-handling capabilities. • Problem Solving & RCA • Technical Expertise in Cloud & Data Engineering • Cross-functional Collaboration • Adaptability to evolving tech • Customer Focus & Escalation Management • Innovation & Automation • Analytical Thinking & Process Optimization

Signals

Skill devops-engineer

0.44

Alias devops-engineer

0.39

KRA cloud-architect

0.46

Post-classification

Centroidupdated · n=25

Alias collision log—

New-role queue—

New skills captured7

New KRA captured—

Captured for admin review

Spark primary ↔ DevOps Engineer pending

Kinesis primary ↔ DevOps Engineer pending

Azure Data Factory primary ↔ DevOps Engineer pending

Blob Storage primary ↔ DevOps Engineer pending

ETL primary ↔ DevOps Engineer pending

ELT primary ↔ DevOps Engineer pending

Time-series data ↔ DevOps Engineer pending

Status: extract_from_jd_done Created: 2026-05-19T01:01:41.013402Z Updated: 2026-05-19T01:01:41.924692Z

Flow Current 3-step pipeline

1 POST /skills/extract-from-jd

2 POST /skills/extract-details

3 POST /skills/final-role-output

Role Chosen role & resolution

No chosen role stored for this run.

Job description

Site Reliability Engineer

Vestas is the world leader in wind technology and a Defining-force in the development of the wind power industry. Vestas’ core business comprises the development, manufacture, sale, marketing and maintenance of Wind Turbines. Come and Join us at Vestas!

Service > Global Service Operations > Security & Platform, Product and Model Operation

The Site Reliability Engineer will ensure the high availability, performance, and reliability of our Scipher platform's infrastructure, supporting seamless operations and customer experiences. The right candidate for the position will bring expertise in incident management, coupled with strong problem-solving abilities and collaboration with development teams to ensure uninterrupted access to our Scipher products' offerings and enhancing overall customer satisfaction.

We count on our site reliability engineers (SREs) to empower users with a rich feature set, high availability, and stellar performance level to pursue their missions. As we expand customer deployments, we are seeking an experienced Site Reliability Engineer to deliver insights from massive-scale data in real time. Specifically, the incumbent will be someone who has fresh ideas and a unique viewpoint, and who enjoys collaborating with a cross-functional team to develop real-world solutions and positive user experiences for every interaction. This Site Reliability Engineer position reports to Operations Manager. This position is based in our Bengaluru, India office.

Responsibilities

Qualifications

• Education & Certification: Bachelor’s or Master’s in Engineering with 4+ years in SRE or related roles. AWS Solution Architect Associate or Azure certification preferred. Familiarity with DevOps tools like Jenkins, Terraform, Ansible.
• Technical Skills: Strong experience with cloud platforms (AWS, Azure), big data technologies (Spark, Kafka, Databricks), and data storage (S3, Blob Storage). Proficient in SQL, Python, Java/Scala, and container orchestration (Kubernetes preferred).
• Soft Skills: Excellent communication, documentation, and time management. Strong problem-solving and customer-handling capabilities.

Competencies

• Problem Solving & RCA
• Technical Expertise in Cloud & Data Engineering
• Cross-functional Collaboration
• Adaptability to evolving tech
• Customer Focus & Escalation Management
• Innovation & Automation
• Analytical Thinking & Process Optimization

What We Offer

You will be a part of a highly dedicated team motivated by creating business value and by developing innovative technical solutions. We offer a place where your dreams of constantly learning can come true. We offer an informal and agile workplace with a high level of freedom in defining the way forward. We expect a lot of our team members when it comes to taking responsibility and ownership of tasks and deadlines, but we stand shoulder by shoulder when celebrating our achievements and mitigating our failures.

Additional Information

The work location is in Bengaluru, India.

Please note: We do amend or withdraw our jobs and reserve the right to do so at any time, including prior to the advertised closing date. Please be advised to apply on or before 30th September 2025.

Learn more about Vestas at www.vestas.com and follow us on our social media channels.

BEWARE – RECRUITMENT FRAUD

It has come to our attention that there are a number of fraudulent emails from people pretending to work for Vestas. Read more via this link, https://www.vestas.com/en/careers/our-recruitment-process

DEIB Statement

At Vestas, we recognise the value of diversity, equity, and inclusion in driving innovation and success. We strongly encourage individuals from all backgrounds to apply, particularly those who may hesitate due to their identity or feel they do not meet every criterion. As our CEO states, "Expertise and talent come in many forms, and a diverse workforce enhances our ability to think differently and solve the complex challenges of our industry". Your unique perspective is what will help us powering the solution for a sustainable, green energy future.

About Vestas

Vestas is the energy industry’s global partner on sustainable energy solutions. We are specialised in designing, manufacturing, installing, and servicing wind turbines, both onshore and offshore.

Across the globe, we have installed more wind power than anyone else. We consider ourselves pioneers within the industry, as we continuously aim to design new solutions and technologies to create a more sustainable future for all of us. With more than 185 GW of wind power installed worldwide and 40+ years of experience in wind energy, we have an unmatched track record demonstrating our expertise within the field.

With 30,000 employees globally, we are a diverse team united by a common goal: to power the solution – today, tomorrow, and far into the future.

Vestas promotes a diverse workforce which embraces all social identities and is free of any discrimination. We commit to create and sustain an environment that acknowledges and harvests different experiences, skills, and perspectives. We also aim to give everyone equal access to opportunity.

To learn more about our company and life at Vestas, we invite you to visit our website at www.vestas.com and follow us on our social media channels. We also encourage you to join our Talent Universe to receive notifications on new and relevant postings.

Skills from this JD

Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.

AWS Primary No API 2 row (run stopped after API 1 or history missing)

Azure Primary No API 2 row (run stopped after API 1 or history missing)

Spark Primary No API 2 row (run stopped after API 1 or history missing)

Kafka Primary No API 2 row (run stopped after API 1 or history missing)

Kinesis Primary No API 2 row (run stopped after API 1 or history missing)

Azure Data Factory Primary No API 2 row (run stopped after API 1 or history missing)

MLflow Primary No API 2 row (run stopped after API 1 or history missing)

Jenkins Primary No API 2 row (run stopped after API 1 or history missing)

GitHub Actions Primary No API 2 row (run stopped after API 1 or history missing)

Terraform Primary No API 2 row (run stopped after API 1 or history missing)

Prometheus Primary No API 2 row (run stopped after API 1 or history missing)

Grafana Primary No API 2 row (run stopped after API 1 or history missing)

Ansible Secondary No API 2 row (run stopped after API 1 or history missing)

Databricks Primary No API 2 row (run stopped after API 1 or history missing)

S3 Primary No API 2 row (run stopped after API 1 or history missing)

Blob Storage Primary No API 2 row (run stopped after API 1 or history missing)

SQL Primary No API 2 row (run stopped after API 1 or history missing)

Python Primary No API 2 row (run stopped after API 1 or history missing)

Java Primary No API 2 row (run stopped after API 1 or history missing)

Scala Primary No API 2 row (run stopped after API 1 or history missing)

Kubernetes Primary No API 2 row (run stopped after API 1 or history missing)

CI/CD Primary No API 2 row (run stopped after API 1 or history missing)

ETL Primary No API 2 row (run stopped after API 1 or history missing)

ELT Primary No API 2 row (run stopped after API 1 or history missing)

MLOps Primary No API 2 row (run stopped after API 1 or history missing)

DevOps Secondary No API 2 row (run stopped after API 1 or history missing)

Time-series data Secondary No API 2 row (run stopped after API 1 or history missing)

Library artifacts (this run)

No artifact rows for this run.

nano JD Parser — gpt-4.1-nano click to toggle

RoleSite Reliability Engineer

CompanyVestas

Experience4+ years in SRE or related roles

DomainEnergy & Utilities

Location Bengaluru, India (onsite)

JD type pass

Certifications

AWS Solution Architect Associate Azure certification

Show raw JSON

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}

API 1 — extract-from-jd click to toggle

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        "matched_count": null,
        "role_id": 1,
        "score": 0.4017,
        "slug": "backend-engineer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "DevOps Engineer",
        "matched_count": 12,
        "role_id": 10,
        "score": 0.4444,
        "slug": "devops-engineer",
        "total_count": 27
      },
      {
        "display_name": "ML Engineer",
        "matched_count": 11,
        "role_id": 3,
        "score": 0.4074,
        "slug": "ml-engineer",
        "total_count": 27
      },
      {
        "display_name": "Data Engineer",
        "matched_count": 9,
        "role_id": 2,
        "score": 0.3333,
        "slug": "data-engineer",
        "total_count": 27
      },
      {
        "display_name": "Cloud Architect",
        "matched_count": 8,
        "role_id": 9,
        "score": 0.2963,
        "slug": "cloud-architect",
        "total_count": 27
      },
      {
        "display_name": "Backend Engineer",
        "matched_count": 8,
        "role_id": 1,
        "score": 0.2963,
        "slug": "backend-engineer",
        "total_count": 27
      }
    ],
    "stage35_ran": false
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "D",
    "chosen_role": {
      "display_name": "DevOps Engineer",
      "matched_count": null,
      "role_id": 10,
      "score": 0.4444,
      "slug": "devops-engineer",
      "total_count": null
    },
    "confidence": 0.92,
    "llm2_fired": true,
    "llm2_reasoning": "The JD\u2019s emphasis on building scalable data and ML pipelines, CI/CD/MLOps, monitoring, automation, and incident management aligns closely with the hands-on responsibilities of a DevOps Engineer.",
    "queued": false,
    "reasoning": "LLM2 picked devops-engineer (confidence 0.92)"
  },
  "stage5_updates": {
    "centroid_n_after": 25,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 1074,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "Spark",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1075,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "Kinesis",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1076,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "Azure Data Factory",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1077,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "Blob Storage",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1078,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "ETL",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1079,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "ELT",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 1080,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "Time-series data",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}

API 2 — extract-details

{}

API 3 — final-role-output

{}

LLM Calls

Every model call made for this run, in pipeline order. Click a card to see the model's response.

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