DevOps AI Engineer

Role Overview: Take full ownership of infrastructure architecture, scaling, and uptime. Establish the technical roadmap, shape and formalize the SRE function, and coach engineers. Design, deploy, and run AI-scale infrastructure that enables real-time healthcare workflows.

Serve as a Founding Member, owning end-to-end infrastructure capabilities and introducing AI-first DevOps, SRE, and MLOps best practices, with direct collaboration alongside the Founder, Co-Founder, and Head of Engineering.

Key Responsibilities:

Architecture & Platform

• Design scalable, secure, cost-efficient AWS/GCP architectures for AI and healthcare workloads
• Lead IaC standards and reusable modules org-wide; own GitOps practices
• Architect optimized Kubernetes (EKS/GKE) for HA, scale, and GPU workload orchestration

Reliability Engineering

• Define and drive reliability targets (SLOs/SLIs); establish SRE practice
• Lead incident management, RCA, and blameless post-mortems for critical systems
• Partner on infrastructure hardening and compliance (SOC 2, HIPAA)

AI-First Engineering

• Lead AI/ML inference and GPU infrastructure scaling in production
• Evaluate and introduce AI tooling, platforms, and automation best practices
• Contribute to LLM deployment pipelines and AI systems reliability

Leadership & SDLC

• Mentor L1/L2 engineers; influence cross-team infrastructure decisions
• Drive DevSecOps maturity across the SDLC (policy-as-code, SBOM, supply-chain security)
• Evaluate and introduce new tooling and platforms

Key Requirements:

• 4–8 years infrastructure/platform/DevOps/SRE
• Deep expertise in AWS & GCP large-scale production systems
• Advanced Kubernetes (cluster design, multi-tenant ops, resource quotas)
• AI/ML inference or GPU infrastructure scaling (production track record)
• Strong Terraform / equiv. and GitOps practices
• Python, Go, or Bash scripting and automation
• Track record in scale, reliability, and cost efficiency
• Lead incident response and on-call practices

Nice-to-Have

• LLM Gateway architecture and optimization
• Zero-trust networking and advanced security/compliance (SOC 2, HIPAA)
• DevSecOps maturity: SBOM, supply-chain security, policy-as-code
• Open-source contributions or platform-team leadership

Why This Role?

• Build infrastructure and products powering real-world healthcare AI
• Work with AI-native engineering teams using cutting-edge tools (Claude Code, Cursor, Copilot)
• Mission-driven impact — improve patient outcomes and save thousands of staff hours
• High ownership, rapid learning, and significant career upside
• Global collaboration across India and the US
• Seed-stage growth — scale from Seed to Series A alongside the team
• Founding Member role and own the entire infrastructure capabilities, including bringing best AI-first practices in DevOps, SRE and MLOps; direct access to work with the Founder, Co-Founder and Head of Engineering

Job Description

Role: Site Reliability Engineer (SRE)

Experience: 8+ Years

Location: Bangalore

Notice Period: Immediate Joiners Only

Key Responsibilities

• Implement reliability practices across applications and cloud platforms.
• Monitor and troubleshoot production systems using observability tools.
• Manage incidents, perform root cause analysis (RCA), and prepare post-incident reports.
• Develop and maintain CI/CD pipelines and automate operational tasks.
• Improve system availability, performance, scalability, and operational stability.
• Develop proof-of-concepts and convert them into production-ready solutions.
• Collaborate with engineering teams to improve reliability and reduce operational toil.
• Use AI tools responsibly to enhance operational efficiency and productivity.

Required Skills

• Strong SRE fundamentals and production support experience.
• Hands-on experience with AWS cloud services and best practices.
• Observability tools: Splunk, Grafana, and Datadog.
• Understanding of metrics, logs/events, and distributed tracing.
• Familiarity with Amazon Connect and contact center technologies, including voice, call recording, and telephony.
• CI/CD tools: Jenkins/Jules; source control: Git/Bitbucket.
• Scripting and automation skills are preferred.
• Experience in incident management, troubleshooting, and RCA documentation.
• Cloud certification or experience supporting cloud-based applications.
• Familiarity with AI concepts and responsible AI tool usage.

Pncpl Software Engineer

Position Responsibilities :

• Lead the architecture and development of AI-powered, distributed systems that meet enterprise-grade performance and security standards.
• Leverage AI tools for code generation, architectural design, and documentation to accelerate delivery and improve quality.
• Design, build, and maintain services using Java following clean-code and secure design principles.
• Develop agentic AI-based tools, domain-specific copilots, and developer productivity enhancements.
• Collaborate with cross-functional teams to define modular, scalable, and compliant architecture patterns.
• Conduct technical design reviews and produce detailed documentation, including system specifications, API docs, and architecture diagrams.
• Integrate AI solutions into CI/CD pipelines, ensuring observability, automated testing, and deployment standards are met.
• Implement robust monitoring and performance engineering practices to maintain high-quality deployments.
• Continuously evaluate emerging AI technologies and integrate them into development workflows for maximum impact.
• Champion best practices in security, automation, and performance optimization across the organization.

Qualifications :

• 6+ years in software engineering with backend development in Java.
• 3+ years with AI tools for development, prototyping, or documentation tasks.
• Experience with cloud-native development and containerized deployment (Docker, Kubernetes).
• Knowledge of AI integration patterns, vector stores, prompt engineering, and RAG pipelines.
• Ability to design software architecture using sequence diagrams, ERDs, data models, and threat models.
• Comfortable with Gen AI-first environments and working with remote Agile teams.

Preferred Qualifications

• Experience building AI copilots or developer tools using OpenAI/Claude SDKs, LangChain, or similar frameworks.
• Experience working in a fast-paced, AIDLC environment, with a strong understanding of CI/CD practices.
• Familiarity with GitHub Actions, Argo Workflows, Terraform, and monitoring/observability tools.
• Containerization and Orchestration: Proficiency in Docker and Kubernetes for containerization and orchestration.
• Cloud Platforms: Experience with cloud computing platforms such as AWS, Azure, or OCI Cloud.

Job Summary 

A Senior Full Stack Observability Engineer – AI Ops & Autonomous Observability to handle / manage , Design and implement enterprise-wide observability across applications, infrastructure, cloud, network, database and digital services. Lead adoption of Datadog, AI Ops, SRE and Autonomous Observability. Build agentic AI and multi-agent orchestration solutions that automate operational workflows and enable autonomous operations.

Technical Skills

• Datadog (Expert)
• OpenTelemetry
• Distributed Tracing
• Application Performance Monitoring
• AI Ops
• LangGraph/CrewAI/AutoGen/Semantic Kernel
• Python
• Azure, AWS
• Kubernetes
• ServiceNow Integration
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Enterprise Observability Strategy

• Define observability standards, governance and operating model.
• Create monitoring roadmaps, service health frameworks, business service dashboards and dependency mapping.
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Full Stack Observability Scope

• Applications, APIs, microservices and user journeys.
• Windows, Linux, VMware, storage and infrastructure platforms.
• Azure and AWS.
• Network monitoring, SQL and NoSQL databases.
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Datadog Platform

• Deploy and optimize Datadog solutions.
• Build dashboards, monitors, alerts and observability-as-code frameworks.
• Integrate Datadog with ServiceNow, Teams and enterprise tooling.
• New Relic exposure is optional.
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AI Ops Responsibilities

• Event correlation and noise reduction.
• Predictive analytics and anomaly detection.
• Incident intelligence and root cause analytics.
• Proactive issue identification and MTTR reduction

Senior Software Engineer – SRE Products (Full Stack)

Work Mode: Remote

Experience: 7+ Years

Employment Type: Full-Time

Job Overview

We are looking for a skilled Senior Software Engineer to join our SRE Product Team. The ideal candidate should have strong expertise in Python, backend development, Node.js/TypeScript and AWS cloud technologies.

The role involves developing scalable applications, automation platforms, observability solutions and reliability engineering tools.

Key Responsibilities

• Design and develop scalable backend applications, REST APIs and microservices.
• Build automation platforms and self-service engineering tools.
• Develop cloud-native applications using AWS services.
• Build frontend interfaces using React or Angular.
• Implement monitoring, observability and application reliability solutions.
• Work with platform and cloud engineering teams to improve system performance.

Required Skills

• 7+ years of software engineering experience.
• Strong hands-on experience in Python.
• Good experience with Node.js, JavaScript and TypeScript.
• Expertise in REST APIs, Microservices and Backend Development.
• Hands-on experience with AWS (Lambda, ECS/EKS, API Gateway, DynamoDB, RDS, CloudWatch).
• Experience with React or Angular.
• Knowledge of Docker, Kubernetes and OpenShift.
• Experience with CI/CD pipelines and Terraform.
• Understanding of SRE principles, monitoring and observability.

Good to Have

• Dynatrace, Prometheus, Grafana, Splunk or OpenTelemetry.
• Experience building internal developer platforms.
• Exposure to AIOps, AI Agents or MCP.

Site reliability engineer - Experience: 8+ Years

Location: Hyderabad / Bangalore

Mandatory Skills: Production Support, SRE, Linux/Unix, AI/ML Infrastructure Knowledge

Position Overview 

The AI Observability Engineer will be instrumental in implementation of scalable, cloud-native solutions to meet the growing needs of our Data & Development team. The successful candidate will demonstrate the ability to abstract complexity and create reusable, scalable patterns that accelerate development. The AI Observability Engineer will build and maintain a robust framework to ensure the reliability and maintainability of DPR Construction's complex AI systems. 

Responsibilities 

• Standardize observability practices across AI/ML and other development teams including logging, metrics, tracing, and model performance monitoring, ingesting data from multiple platforms 
• Lead hands-on implementation of automation-first DevOps and MLOps practices, enabling infrastructure-as-code and consistent, repeatable environment provisioning 
• Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly detection 
• Deploy, maintain and monitor containerized ML workloads 
• Extend existing CI/CD pipelines to support automated infrastructure changes and ML workflows 
• Implement AI-driven data validation, schema and concept drift detection and metadata management. 
• Establish governance frameworks for AI systems, including bias detection, explainability, and auditability 
• Extend existing Azure RBAC strategy by automating role and permission management to reduce manual intervention 
• Develop automated test suites for model performance, regression, edge cases and bias validation 
• Monitor model KPIs (accuracy, precision, recall, latency, calibration) 
• Ensure reproducability of experiments and production models 
• Act as a technical point of contact for DevOps and MLOps practices, developing reusable patterns, documentation, and proof-of-concepts to drive adoption 

Qualifications 

• Bachelor’s degree in computer science, Data Science, Information Systems, or a related field 
• 5+ years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering 
• Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure 
• Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn 

Experience: 8+ Years

Location: Hyderabad / Bangalore

Mandatory Skills: Production Support, SRE, Linux/Unix, AI/ML Infrastructure Knowledge

Job Description:

• Provide production support for mission-critical applications, including incident management, troubleshooting, RCA, deployments, monitoring, and service restoration.
• Implement SRE practices to improve system reliability, availability, and performance.
• Support AI/ML platforms and GPU infrastructure; knowledge of GenAI and AI/ML workloads is preferred.
• Automate repetitive support activities using Python and Shell scripting.
• Monitor systems using tools such as Splunk and AppDynamics.
• Identify performance bottlenecks and drive continuous improvement.
• Collaborate with infrastructure, application, and business teams to resolve production issues.

Required Skills:

• 8+ years of experience in Production Support and SRE.
• Strong Linux/Unix administration and troubleshooting skills.
• Experience with incident management, RCA, monitoring, and automation.
• Knowledge of AI/ML platforms, GPU infrastructure, and GenAI concepts.
• Python/Shell scripting knowledge.
• Exposure to Hadoop, Spark, or Elasticsearch is an advantage.
• Willingness to work in 24x7 shifts.
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Staff Engineer - AI:

Location : India, Remote

Job Description

Egnyte is seeking an experienced Staff Software Engineer to join our Engineering department. The Engineering department builds large distributed components and services that run Egnyte's Cloud Platform. Our code serves billions of requests per day with sub-second latency in a fault-tolerant environment. We process and analyze millions of files and events daily. Some of the responsibilities for this department include Egnyte's Cloud File System, Content Classification, Content Lifecycle Management, User Behavior Analysis, Object Store, Metadata Stores, Search Systems, Recommendations Systems, Synchronization, and intelligent caching of multi-petabyte datasets. We are looking for candidates with a shared passion for building large-scale distributed systems and a keen sense for tackling complexities that come with scaling through multiple orders of magnitude.

In this role, you will (But are not limited to):

• Design and develop highly scalable and resilient cloud architecture that seamlessly integrates with on-premises systems
• Drive the team’s goals and technical direction to find and pursue technical opportunities that make Egnyte’s cloud platform more efficient
• Effectively communicate complex design and architecture details
• Understand company and industry-wide trends to help develop new technologies
• Conceptualize, develop, and implement changes that prevent key systems from becoming unreliable, under-utilized, or unsupported
• Own all aspects of critical software projects from design to implementation, QA, deployment, and monitoring

Qualifications

• BS, MS, or PhD. in Computer Science or related technical field, or equivalent practical experience
• 8-15 years of professional experience in engineering with a history of technical innovation
• Experience providing technical leadership to engineers

Bonus Qualifications (Good to Have)

• The breadth of knowledge across infrastructure domains, with the ability to reason about everything from data center machine software to database solutions to machine learning infrastructure to front-end web or mobile applications
• Demonstrated success in designing and developing large-scale, complex systems
• Expertise with multi-tenant, highly complex, cloud solutions; experience with Hybrid and/or on-premises solutions desired

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

Role Overview

We are looking for an experienced **Site Reliability Engineer (SRE) / Production Support Engineer** with strong expertise in application/production support, incident management, monitoring, cloud operations, automation, and infrastructure technologies.

The candidate will be responsible for ensuring the **availability, reliability, and performance of production applications**, troubleshooting critical issues, monitoring systems, and supporting production deployments.

#### Key Responsibilities & Skills

- Strong experience in **Application / Production Support**.

- Hands-on experience in **Production Issue Handling and Incident Management**.

- Experience in **Batch Monitoring** and production monitoring activities.

- Good understanding of **Network, Load Balancing, and Database-related issues**.

- Strong understanding of **SLI, SLO, Error Budget, and Burn Rate concepts**.

- Hands-on experience with **Splunk queries and dashboard creation/monitoring**.

- Experience with **APM (Application Performance Monitoring) tools**.

- Experience supporting **Production Deployments**, including **Blue-Green and Canary deployments**.

- Good knowledge of **Cloud Operations**.

- Hands-on experience with **Docker, Kubernetes, and Terraform/IaC**.

- Strong knowledge of **Linux/Windows administration and shell scripting**.

- Experience with **Windows administration and scripting**.

- Knowledge of **Python scripting/automation**.

- Exposure to **GenAI tools such as GitHub Copilot, Claude, or similar tools** for day-to-day operational activities.

- Strong troubleshooting, problem-solving, and incident-resolution skills.

Shift Timings

The role involves rotational shifts: