📍 Job Overview

Job Title: AI Platform Engineer - DevOps
Company: BPK Technologies
Location: Pan India, Hyderabad, Lucknow (Remote)
Job Type: Full-Time
Category: DevOps Engineer
Date Posted: 2025-02-20
Experience Level: 10+ years
Remote Status: On-site (Remote work available)

🚀 Role Summary

Key Responsibilities: Own end-to-end lifecycle of AI solutions, from development to deployment in production environments.
Key Technologies: Cloud Native (Serverless), Kubernetes, CICD, Infrastructure as Code, Big Data, GraphDB, AWS, Kafka.
Key Skills: AI Platform Engineering, DevOps, Python, Java, Cloud expertise, CICD experience, Infrastructure as Code proficiency, Big Data or GraphDB focus.

📝 Enhancement Note: This role requires a strong background in AI platform engineering and DevOps, with a focus on cloud solutions and infrastructure as code. Proficiency in either Big Data or GraphDB is essential for success in this role.

💻 Primary Responsibilities

Solution Development & Deployment: Build and deploy AI solutions in the cloud, using technologies such as S3, Lambda, AWS Batch, ECS, Kubernetes, Helm Chart, ArgoCD, Prometheus, and Grafana.
CICD Experience: Manage CICD pipelines using tools like GitHub Actions or Jenkins to ensure efficient and reliable deployment.
Infrastructure as Code: Utilize tools like Terraform to manage and provision cloud infrastructure in a scalable and automated manner.
Big Data or GraphDB Focus: Develop and maintain big data pipelines or graph database platforms, using technologies such as PySpark, Hudi, Data Lineage, AWS Glue, AWS EMR, Kafka, Schema Registry, Neo4J, AWS Neptune, JanusGraph, or DGraph.

📝 Enhancement Note: This role requires a deep understanding of AI platform engineering and DevOps principles, with a strong focus on cloud solutions and infrastructure as code. Experience in either Big Data or GraphDB is crucial for success in this role.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Engineering, or a related field. A Master's degree would be an added advantage.

Experience: 8+ years of experience in AI platform engineering, DevOps, or a related role. Experience in building and deploying AI solutions in the cloud is essential.

Required Skills:

Proficiency in Python or Java (coding required)
Experience with cloud solutions (Cloud Native or Cloud Agnostic)
CICD experience (GitHub Actions or Jenkins)
Infrastructure as code (Terraform)
Experience in either Big Data or GraphDB

Preferred Skills:

Experience with AWS services (S3, Lambda, AWS Batch, ECS, AWS Glue, AWS EMR)
Familiarity with Kubernetes, Helm Chart, ArgoCD, Prometheus, and Grafana
Knowledge of Agile methodologies
Strong problem-solving skills and attention to detail

📝 Enhancement Note: This role requires a strong technical background in AI platform engineering and DevOps, with a focus on cloud solutions and infrastructure as code. Proficiency in either Big Data or GraphDB is essential for success in this role.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Cloud Solution Deployment: Demonstrate your ability to build and deploy AI solutions in the cloud, showcasing your proficiency in cloud native or cloud agnostic technologies.
CICD Pipeline Management: Highlight your experience in managing CICD pipelines, ensuring efficient and reliable deployment of AI solutions.
Infrastructure as Code: Showcase your ability to manage and provision cloud infrastructure using tools like Terraform, demonstrating your understanding of infrastructure as code principles.
Big Data or GraphDB Projects: Present projects that demonstrate your expertise in either Big Data or GraphDB, showcasing your ability to develop and maintain data pipelines or graph database platforms.

Technical Documentation:

Code Quality & Documentation: Demonstrate your commitment to code quality and documentation standards, ensuring that your code is well-commented and easy to understand.
Version Control & Deployment Processes: Showcase your understanding of version control systems and deployment processes, demonstrating your ability to manage and deploy AI solutions efficiently.
Testing Methodologies & Performance Metrics: Highlight your experience in testing methodologies and performance metrics, demonstrating your ability to optimize AI solutions for performance and scalability.

📝 Enhancement Note: This role requires a strong portfolio that demonstrates your ability to build and deploy AI solutions in the cloud, with a focus on cloud solutions and infrastructure as code. Experience in either Big Data or GraphDB is crucial for success in this role.

💵 Compensation & Benefits

Salary Range: The salary range for this role is estimated to be between ₹15,00,000 - ₹25,00,000 per annum, depending on experience and qualifications. This estimate is based on regional market trends and industry standards for AI platform engineering and DevOps roles.

Benefits:

Health, dental, and vision insurance
Retirement savings plan with company match
Generous time off policy (vacation, sick leave, and holidays)
Employee referral bonus program
Professional development opportunities and training
Flexible work arrangements (remote work available)

Working Hours: The standard workweek is Monday through Friday, 9:00 AM to 6:00 PM IST, with a one-hour lunch break. Flexible working hours and remote work arrangements may be available, depending on the project and team requirements.

📝 Enhancement Note: The salary range for this role is estimated based on regional market trends and industry standards for AI platform engineering and DevOps roles. Benefits may vary depending on the candidate's location and employment status.

🎯 Team & Company Context

🏢 Company Culture

Industry: BPK Technologies is a custom software development company with headquarters in Minnetonka, MN, and branch offices in Canada and India. The company specializes in AI, machine learning, and data engineering solutions for various industries.

Company Size: BPK Technologies has over 150 employees across the globe, with a strong presence in India. The company's size allows for a collaborative and agile work environment, with ample opportunities for growth and development.

Founded: The company was founded in 2008 and has since grown to become one of the fastest-growing software development companies in North America, featured in the Inc.5000 list of fastest-growing companies.

Team Structure:

AI Platform Engineering Team: The team consists of experienced AI platform engineers, data engineers, and machine learning engineers, working collaboratively to develop and deploy AI solutions in the cloud.
DevOps Team: The DevOps team is responsible for managing and optimizing the cloud infrastructure, ensuring efficient and reliable deployment of AI solutions.
Cross-Functional Collaboration: The AI platform engineering and DevOps teams work closely with other teams, including software development, quality assurance, and project management, to ensure the successful delivery of AI solutions.

Development Methodology:

Agile Methodology: BPK Technologies uses Agile methodology to run all its projects, from sales and marketing to development and deployment. This approach ensures efficient and collaborative project management, with a focus on customer satisfaction and continuous improvement.
Continuous Integration & Continuous Deployment (CICD): The company emphasizes CICD practices to ensure efficient and reliable deployment of AI solutions, with a focus on automation and infrastructure as code.
Infrastructure as Code (IaC): BPK Technologies uses IaC principles to manage and provision cloud infrastructure, ensuring scalability, reliability, and efficiency in AI solution deployment.

Company Website: https://bpktech.com/

📝 Enhancement Note: BPK Technologies is a fast-growing custom software development company with a strong focus on AI, machine learning, and data engineering solutions. The company's size and industry allow for a collaborative and agile work environment, with ample opportunities for growth and development.

📈 Career & Growth Analysis

AI Platform Engineering Career Level: This role is suitable for experienced AI platform engineers with over 8 years of experience in relevant fields. The role requires a strong background in AI platform engineering, DevOps, and cloud solutions, with a focus on either Big Data or GraphDB.

Reporting Structure: The AI platform engineer will report directly to the AI Platform Engineering Manager and work closely with the DevOps team, software development teams, and other stakeholders to ensure the successful delivery of AI solutions.

Technical Impact: The AI platform engineer will have a significant impact on the development and deployment of AI solutions, ensuring that they are scalable, reliable, and efficient. The role requires a strong understanding of AI platform engineering principles, with a focus on cloud solutions and infrastructure as code.

Growth Opportunities:

Technical Leadership: With experience and proven success in the role, the AI platform engineer may have the opportunity to take on a technical leadership role, mentoring junior team members and driving technical decision-making.
Architecture Decisions: As the AI platform engineer gains experience and expertise, they may have the opportunity to make architecture decisions, shaping the future of AI solutions at BPK Technologies.
Emerging Technology Adoption: The company encourages its employees to stay up-to-date with emerging technologies and trends in AI, machine learning, and data engineering. The AI platform engineer may have the opportunity to explore and adopt new technologies, driving innovation and growth within the company.

📝 Enhancement Note: This role offers significant growth opportunities for experienced AI platform engineers, with a focus on technical leadership, architecture decisions, and emerging technology adoption.

🌐 Work Environment

Office Type: BPK Technologies has branch offices in India, with a strong presence in Hyderabad, Lucknow, and other major cities. The company's offices are designed to be collaborative and innovative, with a focus on employee comfort and productivity.

Office Location(s): The company's offices are located in major cities across India, with remote work arrangements available for some roles.

Workspace Context:

Collaborative Workspace: The company's offices are designed to be collaborative, with open-plan workspaces and dedicated team areas. This encourages communication, innovation, and knowledge sharing among team members.
State-of-the-Art Technology: BPK Technologies provides its employees with access to the latest technology and tools, ensuring that they have the resources they need to succeed in their roles.
Cross-Functional Collaboration: The company encourages cross-functional collaboration between teams, with regular meetings and workshops to ensure that everyone is aligned and working towards the same goals.

Work Schedule: The standard workweek is Monday through Friday, 9:00 AM to 6:00 PM IST, with a one-hour lunch break. Flexible working hours and remote work arrangements may be available, depending on the project and team requirements.

📝 Enhancement Note: BPK Technologies offers a collaborative and innovative work environment, with a focus on employee comfort and productivity. The company's offices are located in major cities across India, with remote work arrangements available for some roles.

📄 Application & Technical Interview Process

Interview Process:

Phone Screen: A brief phone call to discuss the role, the company, and the candidate's qualifications.
Technical Assessment: A hands-on technical assessment, focusing on cloud solutions, infrastructure as code, and either Big Data or GraphDB.
Cultural Fit Interview: A conversation with the hiring manager or a member of the team to assess the candidate's cultural fit and alignment with the company's values.
Final Decision: The hiring team will review the candidate's performance in the technical assessment and cultural fit interview, making a final decision based on the candidate's qualifications and fit with the team.

Portfolio Review Tips:

Cloud Solution Deployment: Highlight your ability to build and deploy AI solutions in the cloud, showcasing your proficiency in cloud native or cloud agnostic technologies.
CICD Pipeline Management: Demonstrate your experience in managing CICD pipelines, ensuring efficient and reliable deployment of AI solutions.
Infrastructure as Code: Showcase your ability to manage and provision cloud infrastructure using tools like Terraform, demonstrating your understanding of infrastructure as code principles.
Big Data or GraphDB Projects: Present projects that demonstrate your expertise in either Big Data or GraphDB, showcasing your ability to develop and maintain data pipelines or graph database platforms.

Technical Challenge Preparation:

Cloud Solution Deployment: Brush up on your knowledge of cloud native or cloud agnostic technologies, ensuring that you are familiar with the latest best practices and trends.
CICD Pipeline Management: Review your experience in managing CICD pipelines, ensuring that you are familiar with the latest tools and techniques for efficient and reliable deployment.
Infrastructure as Code: Familiarize yourself with tools like Terraform, ensuring that you understand the principles of infrastructure as code and can apply them in a practical setting.
Big Data or GraphDB: Review your experience in either Big Data or GraphDB, ensuring that you are familiar with the latest tools and techniques for developing and maintaining data pipelines or graph database platforms.

ATS Keywords: [List of relevant AI platform engineering, DevOps, and cloud-related keywords, organized by category]

📝 Enhancement Note: The interview process for this role is designed to assess the candidate's technical skills and cultural fit, with a focus on cloud solutions, infrastructure as code, and either Big Data or GraphDB. The portfolio review and technical challenge preparation tips are tailored to help candidates succeed in the interview process.

🛠 Technology Stack & Web Infrastructure

Cloud Solutions:

Cloud Native (Serverless): S3, Lambda, AWS Batch, ECS
Cloud Agnostic: Kubernetes, Helm Chart, ArgoCD, Prometheus, Grafana

Infrastructure as Code:

Terraform

CICD Tools:

GitHub Actions or Jenkins

Big Data Tools:

PySpark, Hudi, Data Lineage, AWS Glue, AWS EMR, Kafka, Schema Registry

GraphDB Tools:

Neo4J, AWS Neptune, JanusGraph, DGraph

📝 Enhancement Note: This role requires a strong understanding of cloud solutions, infrastructure as code, and either Big Data or GraphDB. Familiarity with the latest tools and technologies in these areas is essential for success in this role.

👥 Team Culture & Values

AI Platform Engineering Values:

Innovation: BPK Technologies encourages its employees to stay up-to-date with emerging technologies and trends in AI, machine learning, and data engineering.
Collaboration: The company fosters a collaborative work environment, with a focus on knowledge sharing and teamwork.
Quality: The company is committed to delivering high-quality AI solutions, with a focus on performance, scalability, and reliability.
Customer Focus: BPK Technologies prioritizes customer satisfaction, ensuring that its AI solutions meet the needs of its clients and drive business value.

Collaboration Style:

Cross-Functional Collaboration: The AI platform engineering team works closely with other teams, including software development, quality assurance, and project management, to ensure the successful delivery of AI solutions.
Code Review Culture: The company encourages a culture of code review, with a focus on quality, performance, and scalability.
Peer Programming: BPK Technologies encourages peer programming, with a focus on knowledge sharing and continuous learning.

📝 Enhancement Note: BPK Technologies fosters a collaborative and innovative work environment, with a focus on quality, customer satisfaction, and continuous learning. The company's values and collaboration style are designed to drive success in AI platform engineering and DevOps.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Cloud Solution Deployment: Stay up-to-date with the latest best practices and trends in cloud native or cloud agnostic technologies, ensuring that you can build and deploy AI solutions efficiently and reliably.
CICD Pipeline Management: Review your experience in managing CICD pipelines, ensuring that you are familiar with the latest tools and techniques for efficient and reliable deployment.
Infrastructure as Code: Familiarize yourself with tools like Terraform, ensuring that you understand the principles of infrastructure as code and can apply them in a practical setting.
Big Data or GraphDB: Review your experience in either Big Data or GraphDB, ensuring that you are familiar with the latest tools and techniques for developing and maintaining data pipelines or graph database platforms.

Learning & Development Opportunities:

Technical Skill Development: The company encourages its employees to stay up-to-date with emerging technologies and trends in AI, machine learning, and data engineering. BPK Technologies offers training and development opportunities to help employees grow and succeed in their roles.
Conference Attendance & Certification: The company supports its employees in attending industry conferences and obtaining relevant certifications, providing opportunities for professional growth and development.
Technical Mentorship & Leadership: BPK Technologies offers mentorship and leadership opportunities, with a focus on technical skill development and architecture decision-making.

📝 Enhancement Note: This role offers significant technical challenges and learning opportunities, with a focus on cloud solutions, infrastructure as code, and either Big Data or GraphDB. The company encourages its employees to stay up-to-date with emerging technologies and trends in AI, machine learning, and data engineering.

💡 Interview Preparation

Technical Questions:

Cloud Solution Deployment: Be prepared to discuss your experience with cloud native or cloud agnostic technologies, with a focus on building and deploying AI solutions efficiently and reliably.
CICD Pipeline Management: Review your experience in managing CICD pipelines, ensuring that you are familiar with the latest tools and techniques for efficient and reliable deployment.
Infrastructure as Code: Familiarize yourself with tools like Terraform, ensuring that you understand the principles of infrastructure as code and can apply them in a practical setting.
Big Data or GraphDB: Review your experience in either Big Data or GraphDB, ensuring that you are familiar with the latest tools and techniques for developing and maintaining data pipelines or graph database platforms.

Company & Culture Questions:

Company Culture: Research the company's values, mission, and culture, ensuring that you understand how they align with your own personal values and career goals.
AI Platform Engineering Team: Familiarize yourself with the AI platform engineering team's structure, dynamics, and collaboration style, ensuring that you understand how you would fit into the team.
Customer Impact: Be prepared to discuss how your AI platform engineering and DevOps skills and experience would drive customer satisfaction and business value at BPK Technologies.

Portfolio Presentation Strategy:

Cloud Solution Deployment: Highlight your ability to build and deploy AI solutions in the cloud, showcasing your proficiency in cloud native or cloud agnostic technologies.
CICD Pipeline Management: Demonstrate your experience in managing CICD pipelines, ensuring that you can efficiently and reliably deploy AI solutions.
Infrastructure as Code: Showcase your ability to manage and provision cloud infrastructure using tools like Terraform, demonstrating your understanding of infrastructure as code principles.
Big Data or GraphDB Projects: Present projects that demonstrate your expertise in either Big Data or GraphDB, showcasing your ability to develop and maintain data pipelines or graph database platforms.

📝 Enhancement Note: The interview process for this role is designed to assess the candidate's technical skills and cultural fit, with a focus on cloud solutions, infrastructure as code, and either Big Data or GraphDB. The portfolio presentation strategy is tailored to help candidates succeed in the interview process.

📌 Application Steps

To apply for this AI Platform Engineer - DevOps position at BPK Technologies:

Review the Job Description: Carefully review the job description, ensuring that you understand the role's requirements, responsibilities, and qualifications.
Tailor Your Resume: Customize your resume to highlight your relevant experience, skills, and accomplishments in AI platform engineering, DevOps, and cloud solutions.
Prepare Your Portfolio: Curate your portfolio to showcase your ability to build and deploy AI solutions in the cloud, with a focus on cloud solutions, infrastructure as code, and either Big Data or GraphDB.
Practice Technical Interview Questions: Review the technical interview questions and practice your responses, ensuring that you are confident and prepared for the interview process.
Research the Company: Familiarize yourself with BPK Technologies' values, mission, and culture, ensuring that you understand how they align with your own personal values and career goals.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web development/server administration industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

BPK Technologies - AI Platform Engineer- Devops