Dattaram Miruke

Enterprise AI Platform Architecture

• Architected and built a production-grade, multi-tenant AI Platform supporting secure enterprise AI applications, agentic workflows, and cloud-native deployment using Kubernetes and AWS.
• Designed reusable AI platform primitives including model serving, prompt orchestration, workflow execution, retrieval integration, memory services, inference routing, and continuous evaluation pipelines.
• Established reusable platform reference architectures ("golden paths") enabling standardized AI application development, Infrastructure as Code, GitOps deployment, and platform consistency across projects.

LLM Infrastructure & AI Services

• Designed multi-tenant AI infrastructure supporting secure model access, Retrieval-Augmented Generation (RAG), vector search, semantic retrieval, and autonomous AI agent execution.
• Architected a multi-LLM gateway supporting Amazon Bedrock, OpenAI, Anthropic Claude, Gemini, and provider abstraction with policy-based routing, rate limiting, failover, and cost optimization.
• Built enterprise RAG architecture including document ingestion, embedding pipelines, OpenSearch, FAISS, pgvector, and hybrid semantic retrieval.

Agentic AI & Developer Platform

• Developed reusable platform capabilities for LangGraph, LangChain, MCP tool servers, memory management, tool execution, and agent workflow orchestration, enabling enterprise AI automation.
• Built reusable AI platform services that simplify application development through standardized APIs, workflow orchestration, and shared platform components.

AI Governance, Security & Observability

• Implemented AI governance using OPA, RBAC, identity federation, policy enforcement, auditability, prompt security, and responsible AI guardrails.
• Developed AI observability capturing latency, token utilization, hallucination detection, response quality, safety signals, infrastructure utilization, and operational cost.
• Built adversarial evaluation pipelines validating prompt injection resistance, safe tool execution, policy compliance, and model behavior before production deployment.

Cloud Platform Engineering

• Provisioned enterprise AWS infrastructure using Terraform across VPC, EC2, EKS, ECS, IAM, ALB, CloudWatch, S3, EBS, and EFS using GitOps deployment workflows.
• Evaluated managed and self-hosted AI platform technologies, integrating Amazon Bedrock services while balancing scalability, operational complexity, cost, and security.
• Partnered with engineering, platform, and security teams to establish engineering standards, reusable platform components, and operational best practices.

Technologies: Python • AWS (Bedrock, EKS, ECS, EC2, IAM, CloudWatch, S3) • Kubernetes • Terraform • GitOps • LangGraph • LangChain • MCP • OpenSearch • FAISS • pgvector • OPA

• Supported enterprise discovery and large-scale migration from on-premises infrastructure to AWS, establishing scalable, secure foundations for data-intensive workloads, multi-account environments
• Designed multi-region, high-availability AWS architectures supporting mission-critical workloads.
• Led the design and roll out of production-grade EKS and ECS clusters, serverless integration using AWS Lambda and Step Functions.
• Established standards for containerized microservices and event-driven serverless architectures, GitHub Actions pipelines, Terraform modules across multiple teams
• Hybrid networking connectivity between on-prem and AWS using VPN and Direct Connect, supporting database and middle-ware integration.
• Drove platform automation and infrastructure standardization to support high availability, scalability, and operational excellence across ECS and EKS workloads.
• Developed reusable infrastructure libraries, deployment templates, and platform automation components that improved engineering productivity and standardized cloud delivery practices.
• Skills: Cloud & Platforms: AWS (EC2, EKS/ECS, S3, EBS, EFS, RDS, IAM, VPC, ALB/NLB, Route53, CloudWatch), Containers: Docker, Kubernetes, IaC / CI/CD: Terraform, GitHub Actions, CloudFormation, Python, Shell

• Led the design and implementation of cloud-native deployment of pipelines, using event-driven and serverless compute services using AWS Lambda, SNS, SQS, and Step functions using multiple FPGA and hardware-accelerated engineering projects.
• Developed reusable infrastructure-as-code platforms using AWS CDK (Python, TypeScript), improving release velocity, consistency, and platform reliability.
• Embedded observability, metrics, and error-budget tracking (DORA metrics) into delivery pipelines to drive continuous improvement., with CloudWatch
• Optimized AWS resource provisioning and deployment workflows, reducing end-to-end lead time by approximately 20%.
• Skills:
• Programming & Automation: Python, TypeScript, Go, Bash
• AWS Platforms & Services: EC2, S3, AMIs, ECS, ECR, EFS, Lambda, SNS, SQS, Step Functions
• DevOps & CI/CD: AWS CDK, CodeCommit, CodeBuild, CodeDeploy, CodePipeline, Git-based workflows
• Observability & Operations: Amazon CloudWatch, delivery metrics, DORA metrics

• Architected, built, and operated end-to-end CI/CD and deployment pipelines for Cisco MSX (Managed Service Accelerator), a core platform powering enterprise SD-WAN backhaul connectivity at global scale.
• Led containerized microservices and Kubernetes platform operations across multiple product pipelines, spanning AWS and OpenStack environments, with infrastructure automated using Terraform and Ansible.
• Designed and executed performance, scale, and resiliency test frameworks for SD-WAN pipelines, ensuring reliable deployment of physical and virtual network devices and improving overall system resiliency by ~25%.
• Built custom Kubernetes CRDs and controllers to support Chaos Engineering test suites, integrating automated fault injection and stress testing directly into CI/CD pipelines.
• Developed and integrated chaos and resilience tooling that uncovered and resolved critical scalability and stability issues, improving cluster robustness by ~30%.
• Implemented load simulation and failure testing using REST APIs, Gatling, and Scala-based DSLs to validate platform behavior under extreme traffic and failure scenarios.
• Proactively diagnosed and resolved complex defects in high-availability distributed systems, improving application uptime by ~15%.
• Evaluated and compared next-generation CI/CD platforms (Harness, GitHub Actions, GitLab CI, Jenkins X) to modernize delivery pipelines and reduce operational friction.
• Built reusable platform services, deployment automation, and self-service infrastructure capabilities that improved developer productivity and reduced operational toil.
• Environment & Tooling : AWS (EC2, VPC, IAM, EKS, ECS, ECR, S3), OpenStack, Kubernetes, Docker, Terraform, Ansible, Helm, CloudFormation, Jenkins, GitLab CI, GitHub Actions, Prometheus, Grafana, Datadog, ELK Stack, Kafka/Zookeeper, Cassandra, CockroachDB, Python, Go, Bash, Chaos Toolkit, SDN, ETSI/NFV

• Architected and implemented an enterprise-wide monitoring and alerting platform using Nagios XI, improving incident response times by ~40% and enabling seamless collaboration across application, platform, security, and networking teams.
• Led the design of an on-premises cloud architecture delivering high availability and scalability for mission-critical enterprise systems.
• Delivered a cloud platform Proof of Concept (PoC) using OpenStack, Docker, Kubernetes, and Helm, accelerating cloud evaluation and decision-making by ~30%.
• Partnered closely with SRE, network security, and application teams to integrate proactive monitoring and alerting, reducing downtime by ~25% through early detection and faster remediation.
• Developed operational runbooks, incident response standards, post-incident reviews, and reliability practices supporting long-term platform operability.
• Designed and deployed an asset management and vulnerability visibility platform using Tenable/Nessus REST APIs, Python (Flask), SQL, and the ELK stack, reducing asset tracking time by ~50% and improving operational visibility.
• Developed custom Nagios XI plugins and dashboards to monitor middleware and application stacks (e.g., TIBCO/JMS)
• Built a Python-based Linux service (Django + Nginx) to process and filter monitoring logs, optimizing alert ingestion into ServiceNow and improving alert processing latency by 35%.
• Independently designed and deployed a unified monitoring and alerting architecture, consolidating fragmented tooling and achieving an overall ~30% reduction in operational noise and overhead.
• Technologies/Platforms: VMware, OpenStack, Docker, Kubernetes, CNI, Service Mesh, Python(Django, Flask), Perl, Bash, Go, Lua; Nagios XI, ServiceNow, Elastic Stack (ELK), Kafka/Zookeeper, Tenable/Nessus, Nmap, MySQL, Jenkins CI/CD, Linux

• Developed and maintained the Cisco UCS Platform Maintenance Framework (QALi) using Python, enabling scalable and repeatable testing for UCS platforms.
• Contributed to the OpenStack Mercury Installer team, leading installation, troubleshooting, and debugging of OpenStack deployments tailored for telecom environments.
• Designed and implemented a Python-based integration library to support VMware NSX within QALi, extending SDN capabilities and improving framework extensibility.
• Collaborated with the ESC/NFV (Elastic Service Controller) Solution Test Team to automate feature validation and test workflows for the SD-WAN product suite.
• Diagnosed and resolved complex platform and automation issues, delivering new framework features and strengthening the NSX integration layer.
• Worked extensively across Linux-based systems and distributed infrastructure stacks, supporting reliability and automation at scale.
• Technologies & Tools:
• Python, Bash, Linux (RHEL, CentOS, Ubuntu), OpenStack, SDN, VMware NSX, ETSI/NFV, ATS/pyATS, QALi, Eclipse

• Actively participated in Cloud Computing division, focusing on development of HP Helion (based on OpenStack) and CloudSystem .
• Engineered performance and scale test framework in Python, specifically designed for scale and stress testing. This framework comprises approximately 7K lines of Python code and is currently in use for product testing.
• Played pivotal role in development of dynamic updates to HP Cloud platform , enhancing its functionality and efficiency.
• Made significant contribution s to creation of patch generation scripts and development of Ansible playbooks, streamlining system updates and configurations.
• Architecturally designed and developed tools for OpenStack orchestration , as well as performance characterization for large-scale cloud environments.
• Set up and debugged Open vSwitch-based network configurations , demonstrating a comprehensive understanding of OpenStack internals, including installation, development, debugging, and areas related to SDN/NFV.
• Technical Expertise : Proficient in a wide array of technologies, including OpenStack, HP Cloud (OpenStack-based), VMWare/ESX, Sphere, Cloud Platform configuration and operations, Python, Bash, Linux (Ubuntu/RHEL), Eucalyptus/AWS, Ansible, and Chef.

• Led development of product roadmap and technology strategy , steering implementation efforts for life sciences and medical informatics product lines.
• Established new team from scratch, building it into cohesive and effective unit.
• Engaged in evaluating and integrating multiple cutting-edge technologies s into product lines, enhancing their capabilities and market relevance.
• Developed cloud-based computational biology platform to serve as backend for product suite being created , leveraging cloud technologies for advanced computational needs.
• Pioneered adoption of application stacks ( such as Bitnami ), which served as forerunners to container technologies, to accelerate process of product development and deployment.
• Technical Expertise : Gained extensive knowledge in various domains including genomics, grid-based computational biology platforms , In-house Solaris Cluster , BioPerl, medical informatics, parallelization and optimization of algorithms , and AWS (utilized for initial genomics/proteomics analysis).

• Served as the Automation Team Lead , overseeing the Sanity and Integration efforts for Cisco's NX-OS 7K , a Data Center switching product. The role focused on ensuring product and code stability across various release cycles.
• Played a key role in the development and implementation of the NX-OS 7K for consolidated data centers.
• Implemented numerous innovative strategies, notably a semi-automated failure analysis system for test failures . This approach significantly reduced the release test cycle time by approximately 20%.
• Received the micro-VC award within the Cisco business unit in recognition of these innovative contributions.
• Technical Proficiencies : Developed expertise in a range of technologies including various routing protocols ( OSPF, BGP, EIGRP, RIP), L2-L3 layer protocols, TCP/IP stack, and configuration and management of Cisco Switches/Routers. Proficient in Linux, Tcl/Tk, Perl, Cisco IOS/NX-OS , virtualization tools like Virtual Box and VMWare, and automation using Cisco ATS System. Also experienced in using Ixia and Pageant for traffic tests.