Experience
6 - 10 yrs
Job Location
Pune, India
Vacancy
1
Designation
Devops Engineer
Job Type
Not specified
Job Description
DevOps
Product Development Position Overview We are seeking a Senior DevOps Engineer to lead the design, development, and optimization of CI/CD pipelines, cloud infrastructure, and automation solutions for a US Healthcare Revenue Cycle Management (RCM) platform. This role will own infrastructure-as-code (IaC), container orchestration, monitoring, and cloud deployments supporting Claims, Prior Authorization, Scheduling, Coding, Collections, and EDI. You will ensure scalable, secure, and compliance-ready DevOps solutions that enable AI/ML, GenAI, Agentic AI, autonomous agents, multi-agent workflows, bots, and RPA pipelines, delivering autonomous, goal-driven, and self-healing operations across the platform.
Job Roles Responsibilities Cloud Infrastructure Leadership :
- Lead design, implementation, and optimization of cloud infrastructure (AWS, Azure, GCP) for RCM platform modules.
- Implement Infrastructure-as-Code using Terraform, CloudFormation, or equivalent tools.
- Ensure high availability, fault tolerance, and auto-scaling of microservices, AI/ML models, GenAI pipelines, agentic AI, autonomous agents/bots, and RPA workflows.
- Monitor cloud costs and optimize resource utilization for production and non-production environments.
- Architect event-driven and agent-driven infrastructure enabling autonomous monitoring, decision-making, and self-healing operations.
CI/CD Automation :
- Design, implement, and maintain CI/CD pipelines for microservices, AI/ML, GenAI, Agentic AI workflows, autonomous agents, multi-agent orchestration, bots, and RPA automation.
- Automate deployment processes for containerized workloads using Docker and Kubernetes.
- Enable continuous integration and delivery of AI/ML models, GenAI systems, and agentic/autonomous workflows, including training, testing, deployment, memory/context handling, and feedback loops.
- Implement AgentOps practices, including monitoring agent/bot behavior, versioning models/tools, safe rollout/rollback strategies, and auditing.
- Monitor and optimize deployment workflows to ensure low-latency, high-performance, and reliable delivery of AI-driven features and autonomous operations.
Monitoring, Security Compliance :
- Configure monitoring, logging, and alerting for cloud resources, applications, AI agents, and bots.
- Ensure HIPAA, SOC 2, and internal compliance policies are enforced in infrastructure, deployment, and autonomous workflows.
- Maintain audit trails, role-based access controls, and secure secrets management.
- Implement guardrails for autonomous agents, including human-in-the-loop governance for critical decisions.
Microservices, API Integration Oversight :
- Support microservices architectures with event-driven pipelines (Kafka, RabbitMQ) and API integrations.
- Expose AI models, agents, and bots via secure REST APIs / microservices control planes for orchestration and interaction with applications and cloud services.
- Enable agents/bots to coordinate with RPA platforms, cloud services, and AI workflows for autonomous execution.
- Integrate Big Data platforms (Snowflake, Spark, Hadoop, EMR, Redshift) to feed AI agents with logs, telemetry, and operational insights for predictive decision-making.
- Ensure reliable, transactional deployment and configuration changes across distributed systems.
Mentorship Team Leadership :
- Mentor junior DevOps engineers and support cross-functional teams in CI/CD, cloud, AI/GenAI, agentic AI, autonomous bots, multi-agent orchestration, and RPA best practices.
- Conduct code and architecture reviews for infrastructure and pipeline implementations.
- Drive continuous improvement initiatives for operational efficiency, scalability, and security.
Candidate Requirements :
- Bachelor s or Master s degree in Computer Science, IT, or related field.
- 6 10+ years of experience in DevOps, cloud engineering, or infrastructure automation, preferably in US Healthcare / RCM.
- Hands-on experience with cloud platforms (AWS, Azure, GCP), Terraform/CloudFormation, and Kubernetes/Docker.
- Strong understanding of CI/CD pipelines, automated testing, monitoring, and logging.
- Exposure to microservices architectures, event-driven pipelines, and API integrations.
- Experience in AI/ML, GenAI, Agentic AI, autonomous agents, multi-agent orchestration, bots, or RPA workflow deployments is highly preferred.
- Knowledge of HIPAA, SOC 2, and healthcare compliance regulations.
Technical Expertise :
- Cloud Infrastructure: AWS, Azure, GCP, Terraform, CloudFormation, VPC, IAM, Security Groups
- CI/CD Automation: Jenkins, GitHub Actions, GitLab CI, ArgoCD, Ansible, Docker, Kubernetes, AI/ML pipeline automation
- Monitoring Logging: Prometheus, Grafana, ELK Stack, CloudWatch, Datadog, bot/agent activity monitoring
- Microservices, API Integration: REST APIs, .NET Core microservices, Kafka, RabbitMQ, event-driven architectures, agentic control planes
- Big Data Analytics: Snowflake, Spark, Hadoop, EMR, Redshift
- Compliance Security: HIPAA, SOC 2, IAM, secret management, audit trails
- AI/GenAI / Agentic AI / Autonomous Bots / Multi-Agent Systems / RPA: Infrastructure provisioning, deployment, orchestration, memory/context management, feedback loops, and safe execution of autonomous workflows
Skillset :
- Strong analytical and problem-solving skills for distributed, microservices-driven infrastructures.
- Ability to design end-to-end cloud architecture and CI/CD pipelines for complex healthcare RCM modules and autonomous AI/GenAI/agentic AI workflows.
- Experience mentoring junior engineers and collaborating with QA, AI/ML, RPA, autonomous bots, and product teams.
- Excellent communication, compliance-first mindset, and ownership of infrastructure projects.
- High attention to detail, scalability thinking, and strategic foresight.
Strategic Impact :
- Ensure scalable, secure, and compliant infrastructure for all RCM modules.
- Enable CI/CD, AI/ML, GenAI, Agentic AI, autonomous agents, multi-agent orchestration, bots, and RPA workflows with reliable, safe, and auditable automation.
- Reduce production incidents, improve deployment efficiency, and accelerate analytics-driven decisions.
- Support audit readiness, regulatory