Grow With Everestek

Overview

We are looking for mid level DevOPS engineer with experience in building and scaling services on AWS cloud environments. You will be working closely with technical leads to help our team establish DevOps practice.

Responsibilities

• Implementing tools to automate the development, build, testing, integration and deployment pipelines for various applications in production environment to serve the needs of global users
• Implementing automated provisioning of cloud infrastructure on leading providers (e.g. Microsoft Azure, AWS, Google Cloud) while maintaining very high levels of system uptime
• Implementing infrastructure patterns and handling deployment at scale to identify and mitigate performance bottlenecks and scaling pitfalls
• Implementing containerized deployment and orchestration using Docker and Kubernetes
• Using configuration management tools (e.g. Terraform, Ansible) to deploy, configure and manage servers in a high-scale production environment
• Monitoring and analyzing server logs to identify any potential issues
• Develop custom scripts to perform various one-off tasks
• Setup, maintain and own CI/CD process across organization
• Build and enforce DevOps standards across organization
• Keep yourself up to date with latest DevOPs practices and tools
• Implement and improve monitoring and alerting
• Build and maintain highly available systems
• Work on multiple projects across organization
• Prepare for and pass cloud certifications exams
• Mentor and influence team to understand DevOPS aspects of their projects
• Present and communicate the architecture in a visual form

Details

• 4+ years of experience working in at AWS cloud environment
• Experience with hands on programming experience with at least one programming languages such as python, java, NodeJS is good to have
• 4+ years of experience with CI/CD tools
• Experience in deploying microservices based applications using container technologies such as Kubernetes/Docker/ECS is a plus
• Experience in test automation and CI/CD using Jenkins / CircleCI / Travis
• Strong experience working in a linux environment
• Strong understanding of networking, load balancing and security best practices
• Strong understanding of Layer 4/ Layer 7 forward proxy and reverse proxy is a plus
• Experience with in-transit and at-rest data encryption with AWS services is a plus
• Experience in managing proxies (Nginx, Envoy) is a plus
• Deep understanding of version control systems like Git
• Experience with building and maintaining robust monitors for production systems
• Experience with building real time insights and reports against production systems
• Experience with Terraform or Ansible to automate infrastructure setup and code deployments
• Strong understanding of networking, load balancing and security best practices
• Experience in managing large scale relational (MySQL, Postgresql) and NOSQL (DynamoDB, MongoDB) databases
• Having recent cloud certification is a plus

Overview

We are looking for a mid level Java developer. You will be responsible for maintaining and developing new backend micro services (In Java Spring boot or Drop wizard framework) along with developing database schema. You will be working alongside other engineers and developers working on different layers of the infrastructure. Therefore, a commitment to collaborative problem solving, sophisticated design, and the creation of quality products is essential.

Responsibilities

• Strong grasp on Java as a language and knowledge of its quirks
• Strong knowledge of Spring Boot and its extensive feature set is a must
• Strong knowledge of Dropwizard framework
• Working knowledge of CI/CD tools such as Jenkins or anything similar
• Familiarity with AWS and its core services such as EC2, RDS
• Experience writing unit tests along with mocking
• Strong knowledge of designing and building RESTful APIs
• Strong understanding of databases
• Creating database schemas that represent and support business processes
• Strong knowledge of Hibernate to integrate with relational database
• Experience with working in Linux environment
• Understanding of fundamental design principles behind a scalable application
• Familiarity with any NoSQL databases
• Proficient understanding of code versioning tools, such as Git
• Experience working in an agile development environment
• Excellent logical and problem solving skills
• Excellent communication skills is a must
• Excellent writing skills is a must

Details

• Interface with key stakeholders and team to manage end to end development of project
• Develop code in Java using modern frameworks such as Springboot and Dropwizard
• Design, build, and maintain efficient, reusable, and reliable code
• Solving complex performance problems and architectural challenges
• Ensure the best possible performance, quality, and responsiveness of applications
• Identify bottlenecks and bugs, and devise solutions to mitigate and address these issues
• Help maintain code quality, organization, and automatization
• Integration of data storage solutions (MySQL, Dynamo DB)
• Deployment and maintenance in AWS cloud
• Design and build secure REST-APIs that will be consumed by front end applications
• Continuously refactor & improve current code base
• Unit testing of backend applications
• Build Continuous Integration & Continuous Delivery pipeline for all components of the project
• Provide daily status to the stakeholders

Overview

We are looking for a python developer to work on a big data processing platform. You will be responsible for creating and maintaining python libraries and web services that will be an integral part of this platform. We are looking for someone who understands elegance in APIs and experience in building libraries used by other developers.

Responsibilities

• Develop microservices in python using Flask
• Develop common libraries and frameworks in python
• Write reusable, testable and efficient code
• Implementation of security and data protection
• Design and implementation of low-latency, high-availability, and performant applications
• Develop lightweight, cross-browser, responsive user interfaces that talks to RESTful web services
• Design and develop quick mockups
• Improve the existing code and help cleaning up technical debt
• Work closely with test developers to help them write automation scripts using selenium
• Work in a highly agile environment and help the team achieve their sprint goals in any way possible
• Interact with stakeholders to understand requirements
• Prepare and give detailed demos to key stakeholders
• Prepare sprint plans based on the requirements

Details

• 3 years of experience developing applications with Python
• Expert in Python, with knowledge of Flask Python web framework
• Able to integrate multiple data sources and databases into one system
• Understanding of the threading limitations of Python, and multi-process architecture
• Experience with designing and developing REST APIs
• Knowledge of user authentication and authorization between multiple systems, servers, and environments
• Experience in designing database schemas that represent and support business processes
• Strong unit test and debugging skills
• Proficient understanding of code versioning tools such as Git
• Understanding of fundamental design principles behind a scalable application
• Familiarity with event-driven programming in Python
• Experience with pip is plus
• Experience with AWS products such as API gateway, Lambda is plus
• Excellent logical and problem solving skills
• Excellent communication skills is a must

Overview

We are looking for a Data Engineer with strong experience in Python, Relational Database, and AWS to design, build, and maintain scalable data pipelines and data infrastructure. The ideal candidate will have hands-on experience working with large datasets, relational databases, and cloud-based data platforms. In this role, you will work closely with engineering, analytics, and product teams to build reliable data systems that support business intelligence, reporting, and data-driven applications. The role requires strong programming skills, a solid understanding of data modeling and database design, and the ability to operate in cloud-native environments.

Responsibilities

• Design, build, and maintain scalable data pipelines for ingesting, processing, and transforming large datasets.
• Develop and maintain Python-based data processing systems and ETL workflows.
• Design and optimize relational database schemas and queries for performance and scalability.
• Build and maintain data integration pipelines across multiple systems and data sources.
• Ensure data quality, consistency, and integrity through validation and monitoring mechanisms.
• Implement automated workflows for data extraction, transformation, and loading.
• Optimize data processing jobs for performance and reliability.
• Work with engineering teams to integrate data systems with backend services and applications.
• Monitor data infrastructure and troubleshoot data pipeline failures or performance issues.
• Document data architecture, pipelines, and data models.

Details

• Strong proficiency in Python for building data pipelines, data processing workflows, and automation scripts.
• Experience working with relational databases such as PostgreSQL, MySQL, or similar systems.
• Strong knowledge of SQL, including query optimization, indexing strategies, and performance tuning.
• Experience designing and implementing ETL/ELT pipelines for large datasets.
• Hands-on experience with AWS cloud services, including services such as S3, RDS, Lambda, Step Function.
• Understanding of data modeling and schema design for scalable data systems.
• Experience working with large datasets and distributed data processing frameworks (e.g., Pandas, PySpark, or similar tools).
• Familiarity with data pipeline orchestration tools such as Apache Airflow or similar workflow managers.
• Experience with data warehousing solutions such as Redshift, Snowflake, BigQuery, or similar platforms.
• Understanding of data validation, monitoring, and data quality practices.
• Familiarity with version control systems such as Git.
• Experience working with containerized environments such as Docker is a plus.

Overview

We are seeking a skilled QA Automation Engineer with hands-on experience in designing and implementing automated test frameworks. The ideal candidate should have strong expertise in Playwright (Java/TypeScript) or Selenium with Java, experience with API test automation, and solid understanding of CI/CD pipelines. Exposure to modern AI-assisted QA tools is a plus.

Responsibilities

• Design, develop, and maintain automated test scripts using Playwright (Java/TypeScript) or Selenium with Java.
• Build and execute test cases for functional, regression, smoke, and integration testing.
• Develop and maintain API test automation suites using frameworks such as REST Assured, Postman, or Playwright API testing.
• Collaborate with developers, product owners, and DevOps engineers to identify test scenarios and ensure high product quality.
• Integrate automated tests into CI/CD pipelines using tools such as GitHub Actions, Jenkins, GitLab CI, AWS CodeBuild/CodePipeline, etc.
• Participate in requirement analysis, story grooming, and release validations.
• Debug test failures, analyze logs, and identify root causes.
• Ensure test coverage, maintain test documentation, and contribute to continuous test improvement.
• Adopt and experiment with AI-based testing tools (e.g., Testim, Mabl, LambdaTest Smart UI testing, GitHub Copilot for test generation) to enhance QA productivity.
• Report defects in a clear, concise manner and verify fixes once resolved.

Details

• 3–6 years of QA experience with a strong automation background.
• Hands-on experience with Playwright using Java or TypeScript, OR Selenium-based automation using Java.
• Strong understanding of OOP concepts, test automation architecture, and design patterns.
• Experience in API automation with REST principles and tools/frameworks such as REST Assured, Playwright API, Postman Collections, or Karate.
• Experience in CI/CD tools and processes; ability to integrate tests into pipelines
• Familiarity with version control systems such as Git.
• Good understanding of Agile methodologies.
• Strong debugging, analytical, and problem-solving skills.

Nice To Have

• Exposure to AI-powered QA tools, autonomous test generation, or test maintenance accelerators.
• Knowledge of Docker, AWS cloud services, or container-based environments.
• Experience with performance testing tools like JMeter or k6.
• Basic understanding of microservices testing strategies.

What We Offer

• Opportunity to work on modern automation frameworks and evolving QA technologies.
• Collaborative and growth-oriented environment.
• Exposure to AI-driven testing practices and DevOps culture.

Overview

We are seeking a highly skilled GenAI Engineer with strong hands-on experience in building AI agents, orchestrating multi-step workflows, and integrating large language models (LLMs) into production-grade systems. The ideal candidate will have at least 2+ years of experience working with GenAI technologies and frameworks such as LangGraph and LangChain, with solid understanding of multiple LLM ecosystems including Google Gemini, OpenAI, and AWS Bedrock. The candidate will be responsible for designing, building, evaluating, and optimizing GenAI systems—including autonomous agents, RAG pipelines, and custom model deployments—while ensuring that the solutions are reliable, safe, and free from unwanted bias or hallucinations.

Responsibilities

• Design, develop, and orchestrate AI agents using LangGraph and LangChain to automate complex workflows and decision-making processes.
• Build modular agent nodes, tools, memory systems, and workflow orchestration components.
• Implement multi-agent collaboration, event-driven flows, and tool-calling capabilities.
• Work with multiple LLM providers (Gemini, OpenAI, AWS Bedrock) to integrate models into AI workflows.
• Evaluate and select appropriate models based on cost, accuracy, latency, and contextual understanding.
• Fine-tune or customize pre-trained foundation models and deploy optimized variants on AWS Bedrock.
• Implement and improve Retrieval-Augmented Generation (RAG) pipelines using vector databases, embeddings, and document loaders.
• Build scalable retrieval systems that support structured and unstructured data sources.
• Work with MCP (Model Context Protocol) servers to integrate external tools and systems into agent execution.
• Develop pipelines for testing AI agents including hallucination detection, bias detection and mitigation, evaluation benchmarks, and prompt resilience and stability.
• Ensure compliance with internal AI policies, guardrails, and ethical AI guidelines.
• Deploy and monitor AI solutions on AWS (Bedrock, Lambda, ECS, S3, Step Functions).
• Maintain CI/CD pipelines for continuous validation and safe rollout of agent workflows.
• Optimize LLM inference costs through caching, batching, prompt engineering, and routing techniques.

Details

• 2+ years of experience as a GenAI Engineer, ML Engineer, LLM Developer, or similar role.
• Strong hands-on expertise with LangGraph and LangChain for building AI agents or workflows.
• Good understanding of LLMs—OpenAI, Gemini, AWS Bedrock models (Claude, Titan, etc.).
• Practical experience with RAG pipelines, embeddings, vector databases, and retrieval optimization.
• Knowledge of MCP servers and integrating external tools with AI agents.
• Experience testing GenAI systems for hallucinations, bias, factual consistency, and output stability.
• Prior exposure to tuning or customizing pre-trained LLMs and deploying them on AWS Bedrock.
• Knowledge of prompt engineering, tool calling, memory management, and agent architecture.
• Solid programming skills in Python.

Nice To Have

• Experience with LangSmith or similar LLM evaluation platforms.
• Experience in MLOps / GenAI Ops practices.
• Familiarity with vector databases (Pinecone, Weaviate, OpenSearch, Chroma).
• Hands-on experience with API development and microservice architectures.

Soft Skills

• Problem-solving mindset with strong analytical thinking.
• Excellent communication and ability to explain complex AI behavior.
• Ability to collaborate across engineering, product, and data teams.
• Curious, self-driven, and passionate about AI and automation.