Must-Have Skills & Traits Core Engineering Advanced Python skills with a strong grasp of clean, modular, and maintainable code practices Experience building production-ready backend services using frameworks like FastAPI, Flask, or Django Strong understanding of software architecture, including RESTful API design, modularity, testing, and versioning. Experience working with databases (SQL/NoSQL), caching layers, and background job queues. AI/ML & GenAI Expertise Hands-on experience with machine learning workflows: data preprocessing, model training, evaluation, and deployment Practical experience with LLMs and GenAI tools such as OpenAI APIs, Hugging Face, LangChain, or Transformers Understanding of how to integrate LLMs into applications through prompt engineering, retrieval-augmented generation (RAG), and vector search Comfortable working with unstructured data (text, images) in real-world product environments Bonus: experience with model fine-tuning, evaluation metrics, or vector databases like FAISS, Pinecone, or Weaviate Ownership & Execution Demonstrated ability to take full ownership of features or modules from architecture to delivery Able to work independently in ambiguous situations and drive solutions with minimal guidance Experience collaborating cross-functionally with designers, PMs, and other engineers to deliver user-focused solutions Strong debugging, systems thinking, and decision-making skills with an eye toward scalability and performance Nice-to-Have Skills Experience in startup or fast-paced product environments. 2-5 years of relevant experience. Familiarity with asynchronous programming patterns in Python. Exposure to event-driven architecture and tools such as Kafka, RabbitMQ, or AWS EventBridge Data science exposure: exploratory data analysis (EDA), statistical modeling, or experimentation Built or contributed to agentic systems, ML/AI pipelines, or intelligent automation tools Understanding of MLOps: model deployment, monitoring, drift detection, or retraining pipelines Frontend familiarity (React, Tailwind) for prototyping or contributing to full-stack features Show more Show less
Must-Have Skills & Traits Core Engineering Advanced Python skills with a strong grasp of clean, modular, and maintainable code practices Experience building production-ready backend services using frameworks like FastAPI, Flask, or Django Strong understanding of software architecture, including RESTful API design, modularity, testing, and versioning. Experience working with databases (SQL/NoSQL), caching layers, and background job queues. AI/ML & GenAI Expertise Hands-on experience with machine learning workflows: data preprocessing, model training, evaluation, and deployment Practical experience with LLMs and GenAI tools such as OpenAI APIs, Hugging Face, LangChain, or Transformers Understanding of how to integrate LLMs into applications through prompt engineering, retrieval-augmented generation (RAG), and vector search Comfortable working with unstructured data (text, images) in real-world product environments Bonus: experience with model fine-tuning, evaluation metrics, or vector databases like FAISS, Pinecone, or Weaviate Ownership & Execution Demonstrated ability to take full ownership of features or modules from architecture to delivery Able to work independently in ambiguous situations and drive solutions with minimal guidance Experience collaborating cross-functionally with designers, PMs, and other engineers to deliver user-focused solutions Strong debugging, systems thinking, and decision-making skills with an eye toward scalability and performance Nice-to-Have Skills Experience in startup or fast-paced product environments. 2-5 years of relevant experience. Familiarity with asynchronous programming patterns in Python. Exposure to event-driven architecture and tools such as Kafka, RabbitMQ, or AWS EventBridge Data science exposure: exploratory data analysis (EDA), statistical modeling, or experimentation Built or contributed to agentic systems, ML/AI pipelines, or intelligent automation tools Understanding of MLOps: model deployment, monitoring, drift detection, or retraining pipelines Frontend familiarity (React, Tailwind) for prototyping or contributing to full-stack features Show more Show less
Required Technical Skills Java & Spring Boot : Strong hands-on experience with Java 8+, Spring Boot, Spring MVC, RESTful APIs, JPA/Hibernate Microservices & API Design : Proficient in designing and building microservices architectures and REST APIs Containers & Orchestration : Deep understanding of Docker and Kubernetes, specifically Azure Kubernetes Service (AKS) . Azure Cloud Services : Hands-on with Azure App Service, Azure SQL or SQL MI, Key Vault, Application Insights, Monitor, and Logging services DevOps & CI/CD : Experience with Azure DevOps, GitHub Actions, Jenkins, Terraform/ARM/Bicep for infrastructure provisioning Streaming & Messaging : Proficient with Apache Kafka for real-time messaging and stream processing Databases : Strong SQL skills; experience with Azure SQL, Cosmos DB, or similar RDBMS/NoSQL. Monitoring & Logging : Familiar with Prometheus, Grafana, ELK stack, Splunk, App Insights, Azure Monitor Networking Basics : Basic understanding of Azure networking (VNets, Subnets, NSGs, Route tables). Experience & Responsibilities Architect, design, and develop cloud-native microservices using Spring Boot and Java. Build robust REST APIs , ensuring integrations and inter-service communication. Containerize applications with Docker; deploy and manage them on AKS . Implement and orchestrate infrastructure as code (IaC) using Terraform, ARM, or Bicep. Setup and maintain CI/CD pipelines via Azure DevOps, GitHub Actions, or Jenkins. Integrate Kafka for event-driven architectureâdefine producers, consumers, topics, and streaming logic. Configure and monitor Azure resources: SQL MI, App Service, Functions, Key Vault, Azure API Management. Implement logging, tracing, and metrics using ELK, Prometheus, Grafana, Application Insights or Splunk. Participate in Agile/SCRUM ceremonies: sprint planning, stand-ups, code/design reviews, retrospectives. Refactor legacy Java code, enforce quality via SonarQube, unit/integration testing, and best practices. Collaborate cross-functionally with DevOps, QA, SRE, and architecture teams for seamless deployment and support. Qualifications 5+ years in backend development with Java and Spring Boot. Demonstrated experience deploying to Azure environments and managing AKS clusters . Proven track record with Kafka-based architectures and DevOps practices. Familiarity with Azure networking and cloud security practices. Excellent problem-solving, analytical thinking, and communication skills. Nice-to-Have Experience with API Gateway or Azure API Management (APIM). Exposure to microservice design patterns like Circuit Breaker, Saga, CQRS. Knowledge of no-SQL databases , e.g. Cosmos DB, MongoDB. Background in front-end frameworks (React/Angular) a bonus. Certifications: Azure Developer, Kubernetes Administrator, or Kafka Practitioner.
AI/ML & GenAI Expertise 5+ years of experience with machine learning workflows: data preprocessing, model training, evaluation, and deployment Practical experience with LLMs and GenAI tools such as OpenAI APIs, Hugging Face, LangChain, or Transformers Understanding of how to integrate LLMs into applications through prompt engineering, retrieval-augmented generation (RAG), and vector search Comfortable working with unstructured data (text, images) in real-world product environments Bonus: experience with model fine-tuning, evaluation metrics, or vector databases like FAISS, Pinecone, or Weaviate Ownership & Execution Demonstrated ability to take full ownership of features or modules from architecture to delivery Able to work independently in ambiguous situations and drive solutions with minimal guidance Experience collaborating cross-functionally with designers, PMs, and other engineers to deliver user-focused solutions Strong debugging, systems thinking, and decision-making skills with an eye toward scalability and performance Core Engineering Advanced Python skills with a strong grasp of clean, modular, and maintainable code practices Experience building production-ready backend services using frameworks like FastAPI, Flask, or Django Strong understanding of software architecture, including RESTful API design, modularity, testing, and versioning. Experience working with databases (SQL/NoSQL), caching layers, and background job queues. Nice-to-Have Skills Experience in startup or fast-paced product environments. 5+ years of relevant experience. Familiarity with asynchronous programming patterns in Python. Exposure to event-driven architecture and tools such as Kafka, RabbitMQ, or AWS EventBridge Data science exposure: exploratory data analysis (EDA), statistical modeling, or experimentation Built or contributed to agentic systems, ML/AI pipelines, or intelligent automation tools Understanding of MLOps: model deployment, monitoring, drift detection, or retraining pipelines Frontend familiarity (React, Tailwind) for prototyping or contributing to full-stack features
The ideal candidate has strong hands-on expertise in C# and legacy .NET frameworks (WinForms/WPF and ASP.NET Web Forms/MVC), with solid experience in Oracle SQL and PL/SQL (complex queries, packages, triggers, performance tuning) and working knowledge of SQL Server for reporting and analytics. They are comfortable working in on-premises, Windows-based environments with multi-tier client/server architectures, scheduled jobs, and batch processes, and can collaborate closely with DBAs and infrastructure teams. The candidate should be highly capable of reverse engineering large, legacy codebases with limited documentation , tracing end-to-end flows across UI, business logic, data access, and database layers, and performing thorough impact analysis before making changes. Strong debugging skills (logs, profilers, Visual Studio), experience handling business-critical production incidents (L2/L3), and familiarity with version control (Git/TFS) and ITSM tools (e.g., ServiceNow, JIRA) are essential. Experience with Information / lab / quality / operations systems or similar complex transactional applications is a strong plus. Work Timings Flexible timings with willingness to support overlapping hours with US time zones (including occasional off-hours / weekend support as needed). Role Summary We are looking for an experienced Application Developer & Support Engineer to maintain, enhance, and support a suite of business-critical legacy applications . These include: A long-running Laboratory Information System used for environmental and analytical testing. Desktop .NET client applications used for managing organic and inorganic test workflows, sample results, and quality checks. A project/operations dashboard that consolidates lab/project performance data from Oracle and SQL Server for reporting. Web applications (on-prem .NET) used for lab data preparation, operational workflows, and internal employee/HR information. All applications are on-premises , using Oracle as the primary transactional database (with some SQL Server reporting), and have complex, tightly coupled code and data flows that must be understood and handled carefully. The role is a mix of development, enhancement, deep troubleshooting, and L2/L3 production support , with strong emphasis on reverse engineering complex legacy systems and ensuring stability. Technical Capabilities & Competencies Core Technical Skills Strong experience with C# and .NET (legacy frameworks such as .NET Framework, WinForms/WPF and classic ASP.NET Web Forms / MVC). Solid expertise in Oracle Database : Advanced SQL (joins, analytical functions, performance-oriented queries). PL/SQL (procedures, functions, packages, triggers). Understanding of indexing, execution plans, and query tuning. Working knowledge of SQL Server and its use for reporting / analytics. Comfort working in on-premise environments with Windows servers, application servers, and database servers. Complex Code & Flow Handling Proven experience in reverse engineering large, legacy codebases with limited or outdated documentation. Ability to understand and trace multi-layered architectures (UI, business logic, data access, database) and dependencies between modules. Strong debugging skills: Using Visual Studio debuggers, logs, and profilers to trace issues across layers. Diagnosing intermittent production issues (e.g., race conditions, memory leaks, connection pool issues, timeouts). Experience analyzing complex stored procedures and PL/SQL packages to understand business rules implemented at the database layer. Capability to perform impact analysis before changing shared components in heavily reused libraries or database objects. Integration & Architecture Awareness Understanding of client–server architectures , multi-tier applications, and on-prem network constraints. Familiarity with file-based integrations, scheduled jobs, and batch processes commonly used in legacy systems. Basic understanding of authentication/authorization patterns in legacy .NET apps and on-prem environments (Windows auth / forms auth, etc.). Engineering Practices & Tools Hands-on experience with version control systems (Git, TFS, Azure DevOps or similar). Familiarity with work management and ITSM tools (JIRA, ServiceNow, Azure DevOps Boards, etc.) for incidents, problems, and changes. Exposure to CI/CD or at least automated build/deployment pipelines for .NET applications (nice to have for future modernization). Key Responsibilities Application Development & Enhancements Analyze functional and technical requirements for enhancements across lab workflow, operational dashboard, and internal web portals. Design, develop, and unit test new features, reports, and UI changes using C#, .NET (legacy frameworks), Oracle SQL/PL-SQL , and related technologies. Refactor and optimize legacy modules while preserving existing behavior and ensuring regression-free delivery. Participate in code reviews and ensure adherence to coding standards and secure coding practices. Production Support & Incident Management Provide L2/L3 support for incidents, problems, and service requests across all applications in scope. Perform end-to-end analysis of issues (UI → business logic → data access → database) using logs, profilers, and SQL analysis. Perform root cause analysis for recurring problems and propose long-term fixes, not just workarounds. Work within defined SLAs for impact assessment, communication, and resolution, including handling priority incidents during non-standard hours if required. Database & Reporting Develop and maintain Oracle SQL/PL-SQL objects (views, procedures, packages, triggers) used by the applications and reports. Support SQL Server–based reporting components, ensuring consistent data between Oracle transactional systems and reporting layers. Work with DBAs to investigate performance bottlenecks (slow queries, blocking, indexing, statistics, etc.). Release & Change Management Prepare deployment packages, change scripts, and release notes for application and database changes. Coordinate promotion of changes across Dev / Test / Prod environments in line with change management processes. Use version control (Git/TFS or similar) for branching, merging, and maintaining stable baselines. Stakeholder Collaboration & Documentation Work closely with onsite IT teams, business users, QA, and operations teams to clarify requirements and validate solutions. Document technical design, data flows, configuration details, and support runbooks for complex modules. Provide knowledge transfer and onboarding support to other team members as needed. Required Experience 5–8+ years of experience in Application Development & Support in enterprise environments. Demonstrated experience in supporting long-running, business-critical legacy systems with complex business logic and data flows. Experience working in distributed onsite–offshore models with overlapping hours to US teams.
The ideal candidate must have strong hands-on experience with DevOps concepts and Grafana installation, configuration, and dashboard development , including deep knowledge of integrations with Prometheus, Loki, Elastic, CloudWatch, Azure Monitor, and on-prem server/network metrics. They must be skilled in alerting setup, SLO/SLA definition, and incident response models , with a solid understanding of Windows/Linux servers, networks, databases, and hybrid cloud environments. Proficiency in scripting (Python/PowerShell/Bash) , troubleshooting infrastructure performance issues, building repeatable dashboard templates, and optimizing noisy alerts is essential. Strong communication skills and the ability to work with distributed teams to support a 24×7 monitoring model are required. Key Responsibilities 1. Grafana Implementation & Administration Install, configure, and manage Grafana Enterprise/OSS in Client environments. Set up access controls, user roles, folder structure, and data source governance. Configure dashboards, alerting rules, plugins, variables, and templates. 2. Data Source Integration Connect Grafana to all required on-prem and cloud monitoring data sources including: Prometheus / Loki / InfluxDB / Elasticsearch CloudWatch, Azure Monitor, GCP Metrics SQL-based sources Windows/Linux server metrics Network devices & firewalls Work with infra-SMEs to understand each system’s metrics and integrate them correctly. 3. Dashboard & Visualization Development Build high-visibility dashboards for: Server performance & capacity (Windows/Linux) Network health (routers, switches, firewalls) Database monitoring (SQL Server, Oracle, PostgreSQL, MySQL, etc.) Application performance & service health Develop standardized templates and modules for repeatable dashboard creation across teams. 4. Alerting, SLO/SLAs & Incident Response Configure alert rules aligned with Client’ priorities and “North Star” monitoring standards. Define and implement alert thresholds, severity levels, escalations, and routing integrations. Integrate Grafana alerts with ticketing systems (ServiceNow/Jira) and on-call tools (PagerDuty, Opsgenie, Teams). Support the creation of response playbooks and runbooks. 5. Monitoring Architecture & Consolidation Assess existing monitoring tools across acquired entities. Inventory all dashboards, alerts, and metrics and plan their migration into Grafana. Help design the unified Monitoring Command Center for Client. Identify noise, redundant alerts, and opportunities for automation or tuning. 6. 24×7 Monitoring Enablement Prepare dashboards, alert policies, and runbooks to support a follow-the-sun offshore model. Support the Client NOC team in stabilizing monitoring and reducing alert fatigue. 7. Documentation & Knowledge Transfer Create documentation for installation, configuration, dashboards, and alerting rules. Build SOPs, runbooks, and onboarding guides for Client infra teams. Provide KT to onshore and offshore teams. Required Skills & Experience Technical Skills Strong experience with Grafana (administration + dashboards + plugins). Hands-on experience integrating: Prometheus, Loki, InfluxDB, Elastic, or similar metric/log systems Cloud-native monitoring tools (AWS CloudWatch, Azure Monitor, GCP Metrics) On-prem server/network monitoring stacks Good knowledge of: Linux and Windows server administration Networking basics (TCP/IP, SNMP, routing, firewalls) Databases (SQL Server, Oracle, PostgreSQL) Scripting (Python, Bash, PowerShell) Monitoring & Observability Skills Experience designing dashboards for infra health, availability, capacity, and utilization. Strong understanding of alerting concepts: thresholds, SLOs/SLAs, and severity levels. Ability to analyze noisy alerts and implement tuning. Cloud & On-Prem Exposure AWS / Azure / GCP monitoring tools experience. Familiarity with hybrid environments and integrating metrics across multiple data centers. Soft Skills Strong communication skills for working directly with Client onshore teams. Ability to gather requirements from infra, DB, app, and network teams. Problem-solving mindset and ownership of monitoring reliability. Preferred Qualifications Experience in a NOC / Operations Support / SRE / Monitoring Engineer role. Exposure to large enterprise monitoring consolidation projects. Experience integrating Grafana with ServiceNow/Jira/PagerDuty. Experience with infrastructure-as-code (Terraform/Ansible) is an advantage.
Role Overview: As an experienced AI/ML Engineer, you will be responsible for developing and implementing machine learning algorithms to drive business insights and solutions. Key Responsibilities: - Develop and deploy machine learning models for various projects. - Collaborate with cross-functional teams to gather requirements and deliver solutions. - Conduct data analysis and provide insights to improve model performance. - Stay updated with the latest trends and technologies in AI/ML. Qualifications Required: - Bachelor's degree in Computer Science, Engineering, or related field. - Proven experience of at least 1 year in AI/ML projects. - Proficiency in programming languages such as Python, R, or Java. - Strong analytical and problem-solving skills. Please note: Walk-in interviews are scheduled on 28th June 2025 at 10th Floor, Sri Harsha Icon, Financial District, Nanakramguda, Makthakousarali, Telangana, 500032. Kindly report at 10:30 AM.,
We are hiring for multiple roles for Finance department: Accounts Receivable Associate (Experience - 2+ years) Accounts Payable Associate ( Experience - 2+ years) Lead - Accounts Payable (Experience - 3-5 years) Billing Specialist (Experience - 2+ years) Collections Associate (Experience - 2+ years) Payment Reconciliation Analyst (Experience - 2+ years) Interested candidates can apply here or share their updated resume at careers@8thelement.ai