Senior Python developer

🏢 Summary: The offer is for a QA Performance Engineer responsible for planning and executing performance testing, identifying system bottlenecks, and improving overall product quality. The role involves hands-on testing, defect reporting, test environment setup, and collaboration on test strategies and documentation. It requires strong technical expertise in performance testing, programming, and QA processes. 🗂️ Requirements: Competent level in Computer Science, Knowledge of architecture and design patterns, Proficiency in Java or Python, Experience with build automation, Experience with code review processes, Experience with unit testing, Knowledge of IT operations, Experience in test design, Experience in test data management, Experience in bug hunting and bug tracking, Experience with testing doubles, Experience with API testing, Experience with performance testing tools, Ability to execute and analyze performance tests 📃 Skills: Java, Python, API, PerformanceTesting, BuildAutomation, UnitTesting, CodeReview, TestDesign, TestDataManagement, BugTracking, TestingDoubles, ITOperations 🏢 Description: We are seeking a QA Performance Engineer with a strong and specialized skill set. The ideal candidate independently plans and executes performance testing, identifies and reports performance issues, analyzes system bottlenecks, and contributes to the continuous improvement of performance testing processes and overall product quality. Responsibilities: Execute test cases for assigned features or modules, report defects, and collaborate with other engineers to ensure the thorough testing of software applications. Contribute to test planning activities, assisting in estimating effort, defining testing milestones, and actively participating in test strategy discussions. Create and maintain product documentation and guides. Assist in the execution of performance test scenarios and report findings to senior team members. Participate in the setup and maintenance of test environments. Contribute to documentation efforts related to performance testing activities. Min requirements: Competent level in Computer Science, Novice in Architecture and design patterns Competent level in Programming languages (Java/Python) Competent level in Development processes, including Build automation, Code review and Unit testing Competent level in IT Operations Competent level in Quality Assurance: - Test Design and Test Data Management - Bug Hunting and Bug Tracking - Testing doubles - API, Performance Testing Tools and Performance Testing We offer: Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office About us: Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: The role involves owning and maintaining critical GPU libraries (cuDNN, NCCL) within large-scale infrastructure, ensuring seamless integration across multiple GPU generations. The engineer will focus on deep debugging, performance regression analysis, build system maintenance, and automation of benchmarking and library rollouts. This position centers on systems-level C++ development at the intersection of hardware and large-scale AI/ML workloads. 🗂️ Requirements: Strong proficiency in C++ and ability to debug large-scale codebases, Deep understanding of Linux systems programming, Experience with compilation, dynamic and static linking, Knowledge of ELF binaries and shared libraries, Proficiency with Linux CLI, Advanced Bash scripting skills, Ability to triage complex technical issues and perform root-cause analysis, Clear written English (B2+) for technical documentation 📃 Skills: C++, Linux, Bash, CUDA, cuDNN, NCCL, Bazel, Blaze, CMake, ELF 🏢 Description: We are looking for a Software Engineer (C++) to join a high-stakes team supporting the GPU infrastructure of a global Tier-1 Tech Giant . If you are a systems-level expert who thrives on the intersection of hardware and software, this is the role for you. You will be the primary guardian of core GPU libraries ( cuDNN, NCCL ) that serve as the bedrock for large-scale Machine Learning and AI workloads. Your mission is to ensure that cutting-edge GPU architectures are seamlessly integrated and maintain extreme stability across massive hardware fleets, from legacy systems to the latest generations. Responsibilities: Library Integration: Own the end-to-end update lifecycle for critical GPU libraries, managing internal versioning, user migration, and alignment with open-source builds. Triage & Deep Debugging: Act as a technical detective to identify, investigate, and debug performance regressions and functional bugs; create minimal reproducers for escalation to hardware vendors or internal core teams. Build & Infrastructure Maintenance: Manage complex build/linking issues using large-scale build tools and maintain custom patches to ensure seamless integration. Validation & Benchmarking: Rigorously verify new library versions against extensive benchmarking suites and coordinate with high-profile internal partners (e.g., Autonomous Driving units) to validate siloed codebases. Automation & Evolution: Proactively improve regression benchmarking suites and develop automation tooling to reduce manual effort in library rollouts. Technical Documentation: Maintain meticulous records of investigations and keep integration playbooks updated to ensure operational excellence. Min requirements: C++ Proficiency: Strong ability to read, navigate, and debug complex, large-scale C++ codebases. Linux Systems Programming: Deep understanding of compilation, dynamic/static linking, ELF binaries, and shared library management. Systems Environments: Proficiency with Linux CLI and advanced Bash scripting for infrastructure automation. Analytical Depth: Proven track record of triaging ambiguous technical issues and conducting root-cause analysis (RCA). Communication: Clear and concise written English (B2+), essential for documenting complex technical bug reports and coordinating with cross-functional global teams. Would be a plus: Build Systems Mastery: Familiarity with large-scale build tools like Bazel, Blaze, or CMake . GPU Ecosystem: Prior exposure to CUDA, cuDNN, or NCCL architectures is highly advantageous. Hardware Awareness: Experience managing software compatibility and performance across multiple hardware generations. Tooling: Experience with internal data monitoring and bug-tracking systems in a distributed engineering environment. We offer: Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office About us: Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: Senior DevOps Engineer role focused on ensuring production stability and driving automation across multi-cloud environments. The position bridges infrastructure and application support, emphasizing CI/CD optimization, incident management, and elimination of manual operational tasks. Responsibilities include managing deployments, patching, and building automation tools to enhance system reliability. 🗂️ Requirements: Commercial experience with AWS, Azure, or GCP, Strong proficiency in Python, Strong proficiency in Java, Hands-on experience designing and maintaining CI/CD pipelines, Experience with Jenkins, GitHub Actions, GitLab CI, or Azure DevOps, Practical knowledge of container ecosystems, Experience in incident management and production monitoring, Experience executing system deployments and infrastructure patching 📃 Skills: AWS, Azure, GCP, Python, Java, Jenkins, GitHubActions, GitLabCI, AzureDevOps, CI/CD, Containers, Monitoring, Automation, DevOps 🏢 Description: We are looking for a highly skilled Senior DevOps Engineer to take ownership of production stability and drive the aggressive automation of support operations. In this role, you will bridge the gap between infrastructure and application support, ensuring the reliability of multi-cloud environments while eliminating manual operational toil. Essential functions Production Operations & Support: Act as the first line of defense for system reliability. Monitor system health, manage incidents, and troubleshoot complex production issues. Support Automation: Write robust code and scripts to automate routine support activities, system patching, and deployment processes. CI/CD Management: Build, maintain, and optimize deployment pipelines across various tools (Jenkins, GitHub Actions, GitLab CI, Azure DevOps). Deployments & Patching: Execute seamless software deployments and infrastructure patching with minimal downtime. Qualifications Cloud Platforms: Commercial experience managing infrastructure in AWS, Azure, or GCP . Programming Skills: Strong proficiency in both Python and Java (essential for building automation tools and supporting the core application stack). CI/CD Mastery: Solid hands-on experience designing and maintaining pipelines (Jenkins, GitHub Actions, GitLab CI, or Azure DevOps). Containerization: Practical working knowledge of container ecosystems. Ops & Reliability: Deep understanding of incident management, production monitoring, and executing system deployments. We offer Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office About us Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: Opportunity for an experienced Big Data Engineer to design and optimize a high-performance data analytics platform processing petabyte-scale datasets. The role focuses on building robust data pipelines, scalable workflows, and real-time reporting systems using modern Big Data technologies. You will work on performance tuning, data quality, and reliable large-scale data processing solutions. 🗂️ Requirements: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, Proven experience as Data Engineer or similar role, Strong proficiency in Spark, HDFS, Airflow, Solid programming skills in Scala, Experience designing and implementing data pipelines, Experience building continuous reporting systems and dashboards, Knowledge of data warehousing concepts, Ability to optimize and tune data processing systems 📃 Skills: Scala, Spark, HDFS, Airflow, Gradle, Kubernetes, BigData, ETL, DataWarehousing, CI/CD 🏢 Description: Our customer is one of the world’s largest technology companies based in Silicon Valley with operations all over the world. In this project, we are working on the bleeding edge of Big Data technology to develop a high-performance data analytics platform, which handles petabytes datasets. We are looking for an experienced Big Data Engineer. Essential functions Design, develop, and maintain robust data pipelines using: Scala, Spark, HDFS, Gradle, Kubernetes and Airflow Implement scalable and efficient data workflows to support data ingestion, processing, and analysis. Develop and maintain continuous reporting systems and dashboards to provide real-time insights. Collaborate with cross-functional teams to understand data requirements and deliver data solutions. Optimize and tune data processing systems for performance and reliability. Ensure data quality and integrity throughout the data lifecycle. Troubleshoot and resolve data processing and pipeline issues. Stay up-to-date with industry trends and emerging technologies to drive innovation in data engineering. Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience as a Data Engineer or in a similar role. Strong proficiency in Spark, HDFS, Airflow Solid programming skills in Scala. Experience with data pipeline architecture and implementation. Expertise in building and maintaining continuous reporting systems and dashboards. Familiarity with data warehousing concepts and technologies. Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills. Would be a plus DevOps/CICD skills We offer Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office About us Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: The offer is for an experienced Big Data Engineer to design and maintain a high-performance data analytics platform processing petabyte-scale datasets. The role focuses on building scalable data pipelines, optimizing distributed processing systems, and delivering real-time reporting solutions using modern Big Data technologies. The position involves close collaboration with cross-functional teams to ensure reliable, high-quality data workflows. 🗂️ Requirements: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, Proven experience as a Data Engineer or similar role, Strong proficiency in Spark, HDFS, Airflow, Strong programming skills in Scala, Experience with data pipeline architecture and implementation, Experience building continuous reporting systems and dashboards, Familiarity with data warehousing concepts, Ability to optimize and tune distributed data processing systems 📃 Skills: Scala, Spark, HDFS, Airflow, Gradle, Kubernetes, BigData, DataWarehousing, CI/CD 🏢 Description: Our customer is one of the world’s largest technology companies based in Silicon Valley with operations all over the world. In this project, we are working on the bleeding edge of Big Data technology to develop a high-performance data analytics platform, which handles petabytes datasets. We are looking for an experienced Big Data Engineer. Essential functions Design, develop, and maintain robust data pipelines using: Scala, Spark, HDFS, Gradle, Kubernetes and Airflow Implement scalable and efficient data workflows to support data ingestion, processing, and analysis. Develop and maintain continuous reporting systems and dashboards to provide real-time insights. Collaborate with cross-functional teams to understand data requirements and deliver data solutions. Optimize and tune data processing systems for performance and reliability. Ensure data quality and integrity throughout the data lifecycle. Troubleshoot and resolve data processing and pipeline issues. Stay up-to-date with industry trends and emerging technologies to drive innovation in data engineering. Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience as a Data Engineer or in a similar role. Strong proficiency in Spark, HDFS, Airflow Solid programming skills in Scala. Experience with data pipeline architecture and implementation. Expertise in building and maintaining continuous reporting systems and dashboards. Familiarity with data warehousing concepts and technologies. Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills. Would be a plus DevOps/CICD skills We offer Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office About us Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: Senior Big Data Developer role focused on full ownership of a modern AWS-based data platform, including architecture, infrastructure, and performance optimization. The position involves building end-to-end data pipelines, managing cloud infrastructure as code, and implementing a scalable data lakehouse using advanced big data frameworks. The role emphasizes deep AWS expertise, Spark-based processing, and workflow orchestration in a high-performance environment. 🗂️ Requirements: Expert-level Core Python proficiency, Strong experience with PySpark and Apache Spark, Extensive hands-on experience across AWS services (S3, Lambda, EMR, Redshift, Glue, VPC, ECS, ECR, SQS), Strong proficiency in AWS CDK and AWS CLI, Experience designing and managing Airflow workflows, Experience with Apache Iceberg table format, Advanced SQL skills, Experience with REST API integration, Proficiency in Bash scripting, Experience with infrastructure-as-code and cloud security (IAM, KMS, Secrets Manager) 📃 Skills: Python, PySpark, Spark, AWS, S3, Lambda, EMR, Redshift, Glue, VPC, ECS, ECR, SQS, CDK, CLI, Airflow, StepFunctions, Iceberg, SQL, REST, Bash, IAM, KMS, Athena, RDS, Pydantic, Alembic 🏢 Description: We are looking for a Senior Big Data Developer to join our team and take full ownership of a modern, high-performance data platform. Essential functions End-to-End Data Engineering: Design and build complex ingestion and transformation pipelines using Python (PySpark) and Apache Spark. Cloud Infrastructure Ownership: Take full responsibility for our AWS environment, utilizing AWS CDK to manage everything from VPCs and Load Balancers to EMR clusters and ECS containers. Orchestration & Workflow: Develop and manage sophisticated data workflows using Airflow (MWAA) and AWS Step Functions. Modern Data Lakehouse: Implement and optimize storage layers using Apache Iceberg and Redshift, adhering to Medallion Architecture and advanced design patterns. Infrastructure-as-Code: Architect self-healing and scalable infrastructure through AWS CDK, ensuring security and compliance via IAM, KMS, and Secret Manager. Performance Tuning: Monitor and optimize query performance across Athena, Glue, and RDS to ensure low-latency data access. Qualifications Python Mastery: Expert-level proficiency in Core Python, including experience with Pydantic and Alembic. Deep AWS Expertise: Extensive hands-on experience across the AWS ecosystem (S3, Lambda, EMR, Redshift, Glue, VPC, ECS, ECR, SQS). IaC & Automation: Strong proficiency in AWS CDK and the AWS CLI; ability to manage your own cloud infrastructure independently. Big Data Frameworks: Proven experience with Apache Spark (PySpark) and modern table formats like Apache Iceberg. Data Orchestration: Hands-on experience with Airflow for managing complex data lifecycles. SQL & APIs: Advanced SQL skills and a solid understanding of REST API integration. Scripting: Proficiency in Bash for system-level automation. Would be a plus Backend Engineering Background: Prior experience in software engineering (beyond just data) is a major plus, specifically building scalable microservices. Familiarity with distributed design patterns and data governance. We offer Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office About us Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: The offer is for an experienced Big Data Engineer to design and maintain a high-performance data analytics platform processing petabyte-scale datasets. The role focuses on building scalable data pipelines, optimizing distributed systems, and delivering real-time reporting solutions using modern Big Data technologies. You will work on cutting-edge data engineering challenges in a large-scale, global environment. 🗂️ Requirements: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, Proven experience as Data Engineer or similar role, Strong proficiency in Spark, HDFS, Airflow, Strong programming skills in Scala, Experience with data pipeline architecture and implementation, Experience building continuous reporting systems and dashboards, Knowledge of data warehousing concepts, Ability to optimize and tune distributed data systems, Experience ensuring data quality and integrity, Ability to troubleshoot complex data pipeline issues 📃 Skills: Scala, Spark, HDFS, Airflow, Gradle, Kubernetes, BigData, ETL, DataWarehousing, Dashboards 🏢 Description: Our customer is one of the world’s largest technology companies based in Silicon Valley with operations all over the world. In this project, we are working on the bleeding edge of Big Data technology to develop a high-performance data analytics platform, which handles petabytes datasets. We are looking for an experienced Big Data Engineer. Responsibilities: Design, develop, and maintain robust data pipelines using: Scala, Spark, HDFS, Gradle, Kubernetes and Airflow Implement scalable and efficient data workflows to support data ingestion, processing, and analysis. Develop and maintain continuous reporting systems and dashboards to provide real-time insights. Collaborate with cross-functional teams to understand data requirements and deliver data solutions. Optimize and tune data processing systems for performance and reliability. Ensure data quality and integrity throughout the data lifecycle. Troubleshoot and resolve data processing and pipeline issues. Stay up-to-date with industry trends and emerging technologies to drive innovation in data engineering. Requirements : Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Proven experience as a Data Engineer or in a similar role. Strong proficiency in Spark, HDFS, Airflow Solid programming skills in Scala. Experience with data pipeline architecture and implementation. Expertise in building and maintaining continuous reporting systems and dashboards. Familiarity with data warehousing concepts and technologies. Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills. Ability to work independently and in a remote team environment. We offer: Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office About us: Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: Site Reliability Engineer role focused on leading the cloud platform layer of a large-scale enterprise migration to GCP, with full ownership of observability and FinOps capabilities. The position involves architecting cost attribution, distributed tracing, monitoring, and performance engineering solutions in a production-grade Kubernetes environment. You will work on complex distributed systems, extending multi-language codebases and managing infrastructure as code in a regulated enterprise setting. 🗂️ Requirements: 4–6 years software or DevOps engineering experience, 2–3 years hands-on cloud infrastructure management in production, Strong GCP expertise including GKE and Cloud Run, Proven experience building observability solutions with OpenTelemetry, Experience with distributed tracing and profiling in distributed systems, Advanced Python scripting for automation and tooling, Strong Terraform proficiency with multi-environment setups, Ability to read and modify Kotlin and Java codebases, Experience implementing monitoring, alerting, and SLOs for containerized/serverless services, Experience with infrastructure cost attribution and cloud billing APIs 📃 Skills: GCP, GKE, CloudRun, Kubernetes, OpenTelemetry, Terraform, Python, Kotlin, Java, FinOps, PubSub, Bigtable, Docker, SLO, Tracing 🏢 Description: We are looking for a Site Reliability Engineer to join a high-stakes global tech ecosystem and drive the delivery of a critical enterprise platform migration to the cloud. Your core mission will be to architect, build, and productionalize the observability and cost intelligence (FinOps) layer for a massive, multi-year financial platform transformation. You will take end-to-end ownership of the cloud platform layer, giving internal stakeholders full visibility into platform behavior, performance, and infrastructure spend. Working alongside a nearshore team of senior engineers, you will solve highly complex architectural challenges in a production-grade, distributed system. Responsibilities: End-to-End Infrastructure & FinOps Ownership: Architect and implement a cloud usage and cost attribution dashboard, providing detailed per-pod and per-service cost breakdown using cloud billing APIs and internal FinOps hubs. Advanced Observability & Tracing: Instrument end-to-end distributed tracing using OpenTelemetry, configuring collectors within Kubernetes environments and exporting traces to cloud monitoring systems utilizing RED metrics. Performance Engineering & Stress Testing: Write custom tooling from scratch to deliver database performance monitoring, load testing, and trend analysis for critical underlying storage layers. Monitoring & Alerting Automation: Build and deploy scalable production monitoring, custom alerting policies, and SLO tracking for containerized and serverless services. Infrastructure as Code: Independently manage, write, and apply infrastructure modifications using Terraform, working within established enterprise repository standards, modules, and environment state management. Cross-Language Codebase Extension: Read, debug, and extend existing platform code across a diverse stack including Kotlin, Java, and Python to seamlessly integrate technical metrics without disrupting business logic. Quality & Release Assurance: Implement rigorous unit testing with high code coverage for all newly developed monitoring tools to comply with strict enterprise quality gates and sign-offs. Min requirements: Experience: 4 to 6 years of professional software or DevOps engineering experience, with at least 2 to 3 years of hands-on cloud infrastructure management in production. Advanced Cloud Infrastructure: Deep operational proficiency with Google Cloud Platform (GCP), specifically with managing and configuring workload-level alerting on Google Kubernetes Engine (GKE) and Cloud Run. Observability & OpenTelemetry: Proven track record of building observability solutions in distributed systems, using OpenTelemetry (both auto and manual instrumentation) alongside distributed tracing and profiling tools. Strong Automation Scripting: Intermediate-to-advanced fluency in Python for writing custom test tooling, metrics integration scripts, and backend automation from scratch. Solid Infrastructure as Code: Strong proficiency in Terraform, including experience with multi-environment setups, workspaces, and corporate module standards. Polyglot & JVM Familiarity: Practical ability to read, understand, and modify existing backend codebases written in Kotlin and Java. Crucial Non-Technical Skills: Extreme technical autonomy to resolve blockers independently, rapid onboarding skills into large unfamiliar codebases, and fluent written English for async alignment and pull requests. Process Alignment: Ability to thrive in a highly regulated enterprise environment with strict peer reviews, robust documentation requirements, and formal deployment procedures. Would be a plus: Domain Knowledge: Previous experience working within financial services, fintech, investment banking, or other highly regulated industries. Enterprise Streaming Tools: Working knowledge of cloud messaging systems (such as Cloud Pub/Sub) utilized for inter-service communication. Advanced Storage Engines: Familiarity with high-throughput distributed database architectures, such as Google Cloud Bigtable. Systems Languages Awareness: Ability to read or debug foundational code written in low-level systems languages like Rust or C++ during multi-stack production deployments. We offer: Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office About us: Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: Senior Python Engineer role focused on building scalable, secure backend systems and infrastructure for a machine learning platform in a global fintech environment. The position centers on developing production-grade services, real-time data pipelines, and cloud-native platform capabilities that enable ML model deployment and monitoring. The role supports low-latency, high-availability systems such as fraud detection. 🗂️ Requirements: Strong commercial experience building production-grade backend systems in Python, Experience designing and operating distributed systems, Practical experience with AWS services (EKS, S3, Lambda), Experience with Docker and Kubernetes, Experience with databases, data pipelines, or streaming platforms, Knowledge of testing methodologies and CI/CD practices, Ability to work in high-availability, regulated environments 📃 Skills: Python, FastAPI, Microservices, DistributedSystems, AWS, EKS, S3, Lambda, Docker, Kubernetes, Kafka, Flink, Databases, Streaming, CICD, GitOps, GitHub, ArgoCD, Datadog, Observability 🏢 Description: We are looking for a Senior Python Engineer to join our ML Platform team. You will be responsible for building the backend systems and infrastructure that power machine learning across a global fintech project. This is a platform engineering role focused on building scalable, reliable, and secure systems that enable ML engineers and data scientists to develop, deploy, and operate models in production. Your work will directly support low-latency, real-time environments, such as fraud detection. Please note: Prior Machine Learning experience is NOT required! If you are a strong backend engineer with an interest in data-driven platforms and ML systems, this is the perfect role for you. Responsibilities: Backend Development: Design and build production-grade Python services (FastAPI / microservices) that support the ML lifecycle, including feature computation, model inference, and monitoring. Real-Time Data Pipelines: Develop and operate data pipelines to support low-latency, high-availability use cases (like fraud detection) using event-driven architectures (Kafka, Flink). Platform Engineering: Build capabilities to enable online and offline feature stores, working closely with Data Engineering to ensure reliable data flows. Developer Experience (DevEx): Improve the daily lives of ML engineers and data scientists through better tooling, automation, and self-service APIs. Cloud & DevOps: Build and maintain CI/CD pipelines (GitOps, GitHub Actions, ArgoCD) and ensure the observability (Datadog), resilience, and scalability of platform services. Security & Compliance: Collaborate with Infrastructure and Security teams to ensure all systems meet strict financial and regulatory standards. Min requirements: Python Mastery: Strong commercial experience in building production-grade backend systems and microservices in Python (this is not a scripting role). Distributed Systems: Proven experience designing, building, and operating backend services or distributed systems. Cloud & Containerization: Solid practical experience with AWS (EKS, S3, Lambda) and container orchestration ( Docker, Kubernetes ). Data Systems: Experience working with databases, data pipelines, or streaming platforms. Engineering Best Practices: Solid understanding of testing methodologies, CI/CD, and code quality standards. High-Availability Focus: Ability to work in highly regulated, high-availability environments where system resilience is critical. Would be a plus: Experience with real-time streaming technologies (Kafka, Flink) and low-latency systems. Background in fintech, payments, risk systems, or fraud detection. Experience with ML platforms/tools (e.g., SageMaker, Ray, Tecton) or exposure to feature stores (online/offline architectures). A general understanding of the machine learning lifecycle (training, inference, feature engineering). We offer: Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office About us: Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

🏢 Summary: Senior Python Engineer focused on building and orchestrating autonomous AI agents that automate the full software development lifecycle using multi-agent architectures and Generative AI. The role involves designing, implementing, and optimizing AI-driven workflows, ensuring observability, reliability, and production readiness. You will work hands-on with advanced AI frameworks and containerized environments to deliver cutting-edge agentic systems. 🗂️ Requirements: Proven experience building or implementing AI agents or workflows using LangGraph or similar frameworks, Strong hands-on software development experience in Python, Practical experience with LangSmith for observability and debugging of AI chains, Strong proficiency with Generative AI tools such as Claude or GPT, Advanced Prompt Engineering skills, Experience designing and optimizing multi-agent architectures, Proficiency in Bash or Shell scripting, Strong experience with Docker and containerization, Ability to integrate AI solutions into production environments 📃 Skills: Python, LangGraph, LangSmith, Docker, Bash, Shell, Claude, GPT, GenerativeAI, PromptEngineering, Java, .NET, Angular, Maven, Gradle, CI/CD, AWS, Azure, GCP 🏢 Description: We are seeking a Senior Python Engineer (AI Automation focus) to join our innovative team in building a cutting-edge autonomous AI agent. This "digital software engineer" is designed to handle the entire development lifecycle—from requirement analysis to production-ready code—using a sophisticated multi-agent architecture. In this role, you will go beyond traditional coding by developing and orchestrating specialized AI components that plan, write, and validate software. You will be at the forefront of the Agentic AI revolution, working for a global leader in the payment industry to redefine how software is built. Tech Stack: Python, LangGraph, LangSmith, Generative AI (Claude Code, OpenAI, etc.), Docker, Bash/Shell, Prompt Engineering, and multi-stack exposure (Java, .NET, Angular). Responsibilities: Design and develop autonomous AI agents using Python and advanced orchestration frameworks like LangGraph. Build and optimize multi-agent architectures where specialized AI components handle requirements, planning, coding, and testing. Implement observability and monitoring for AI workflows using LangSmith to ensure high-quality and reliable agent performance. Hands-on utilization and integration of Generative AI tools (Claude Code, etc.) to drive the "AI-building-AI" vision. Conduct complex prompt engineering to fine-tune the agent’s decision-making and coding capabilities. Containerize applications using Docker and manage environments with proficient Bash/Shell scripting. Collaborate with cross-functional teams to integrate the AI agent into production environments and diverse tech stacks. Maintain an adaptive mindset, proactively solving challenges in an evolving, fast-paced R&D setting. Min requirements: Proven experience building or implementing AI agents/workflows using frameworks like LangGraph. hands-on software development experience with Python . Strong proficiency in Generative AI tools (Claude, GPT, etc.). Practical experience with LangSmith for observability and debugging of AI chains. Advanced skills in Prompt Engineering and building autonomous logic. Proficiency in Bash and Shell scripting for environment management. Strong experience with containerization using Docker . Ability to work with an adaptive mindset , comfortably switching between different technical challenges. Would be a plus: Multi-stack literacy: Basic knowledge of Java (Maven/Gradle), .NET, or Angular to help the AI agent navigate diverse codebases. Experience in the Fintech or Payment Processing industry (understanding of secure coding and financial systems). Knowledge of CI/CD pipelines and automated testing at scale. Experience with distributed systems and cloud infrastructure (AWS, Azure, or GCP). Contributions to AI-related open-source projects or LLM research. We offer: Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office About us: Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI , supported by profound expertise and ongoing investment in data , analytics , cloud & DevOps , application modernization and customer experience . Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.