Feb 2026 – Present · 3 mos

• Heading the AI & Data Engineering Team in Technology Standards – Research & Innovation – AI & Platforms, where I lead the development of core AI, data, and platform capabilities that underpin Nokia’s shift toward an AI‑first R&I organization. This includes evolving the AgentOps and Agentic AI frameworks, architecting common AI & data platforms, enabling cloud‑native simulation environments, and building scalable data engineering pipelines that power research, standardization, and next‑generation AI workflows.

Apr 2024 – Feb 2026 · 1 yr 10 mos

• Core Competencies
• System Architecture: Proficient in designing robust and scalable systems with detailed blueprints of components, interfaces, and communication protocols. Expertise in selecting optimal technologies, frameworks, and tools tailored to project demands while documenting best practices for long-term architectural alignment.
• Cloud and Containerization Expertise: Skilled in Docker, Kubernetes, and cloud-native design patterns to build efficient, scalable, and resilient solutions.
• Microservices Architecture: A design-first advocate, implementing microservices-based architectures, RESTful APIs, and utilizing Swagger/OpenAPI for documentation, testing, and collaborative development.
• MLOps, LLMOps, AIOps, and Automation: Hands-on expertise in architecting automation workflows across the ML and GenAI lifecycle, including data ingestion, preprocessing, training, deployment, monitoring, and continuous retraining. Experience with tools like Kubeflow, MLflow, AWS SageMaker, Langfuse for LLM observability, and vector databases for semantic retrieval. Skilled in building highly reliable LLMOps and AIOps frameworks for large-scale AI deployments.
• GenAI, Agentic AI & Orchestration Frameworks: Strong experience with modern GenAI stacks, including LangChain, LangGraph, and Langfuse for developing agentic workflows, RAG pipelines, evaluation frameworks, and production-ready LLM-based systems. Expertise in retrieval-augmented generation (RAG), reasoning agents, tool orchestration, and multi-agent collaborative architectures.
• Data & Search Technologies: Proficient in PostgreSQL, vector databases (Pinecone, FAISS, Milvus, pgvector), and Elasticsearch for designing scalable knowledge retrieval systems, semantic search, and enterprise-grade data architectures.
• Strong foundation in security, scalability, and performance optimization for AI/ML, GenAI, and large-scale distributed systems.

Apr 2022 – Apr 2024 · 2 yrs

• Working and contributing to various areas of product development:
• System Architecture
• Craft detailed blueprints for the system, including components, interfaces, and communication protocols.
• Evaluate and choose suitable technologies, tools, and frameworks based on project needs and constraints.
• Guide and mentor development teams on implementing the architectural designs.
• MLOps
• Defining the overall MLOps strategy, collaborating with stakeholders to understand business needs and translate them into technical requirements for an MLOps pipeline.
• Choosing and integrating tools and technologies, selecting appropriate tools for data pipelines, model training, deployment, monitoring, and governance.
• Designing automation workflow architecture, automating various stages of the ML lifecycle, including data ingestion, preprocessing, model training, deployment, and feedback loops.
• ​​​​​​Building versatile ML development and AI deployment setups (pipelines and/or platforms) and other MLOps solutions to enable production-level AI and ML in multi-cloud environments.
• Optimizing infrastructure, building robust and scalable infrastructure for efficient model training and deployment.
• Training and mentoring teams, educating stakeholders on MLOps principles and best practices to foster a culture of automation and observability.

Mar 2020 – Apr 2022 · 2 yrs 1 mo

• Design and Development of SON and Network Management Systems.
• Identification of Machine Learning use cases, developing prototypes and executing PoC at
• customers.
• Preparation of MLOps workflows (pipeline) for SON production deployments.
• Preparation of feature specifications of security and ML related features.
• Transformation of the classic SON to cloud native architecture.
• Coaching & Mentoring team and developing talent.
• Gathering Industry, Market & Technology Insights.
• Worked on the following ML use cases in SON:
• ML enabled root cause analysis and classification with automated remediation.
• ML based mobility load balancing (MLB).
• KPI prediction service using ANN enhanced with Embedding.
• Reinforcement Learning based mobility load balancing (RL-MLB) using Q-Learning.

Dec 2015 – Feb 2020 · 4 yrs 2 mos

• Actively involved in architecture, design and development of EdenNet SON solution.
• Nokia EdenNet lets operators automate operations and realize the full potential of their existing
• 2G, 3G, 4G networks while supporting the transformation to 5G.
• Providing a centralized SON platform, it automates operations across multiple technologies,
• eliminating complexities from multi-vendor and multi-layered networks.
• The wide range of ready-made SON modules take self-configuring, self-healing and self-
• optimizing actions that boost network performance and efficiency.

Jan 2013 – Nov 2015 · 2 yrs 10 mos

• Worked on a Platform (developed from scratch) and common services which were used by
• various OSS products at Nokia.
• Started learning and working on Nokia EdenNet SON solution.

Aug 2010 – Dec 2012 · 2 yrs 4 mos

• Worked on Nokia's NetAct. Nokia's NetAct is a field proven network management system that
• offers best-in-class applications for seamless daily network operations, including configuration
• management, monitoring and software management. NetAct supports network elements in
• mobile radio and core, Wi-Fi, IoT, public safety and telco cloud. I worked on following
• components of NetAct (OSS):
• Adaptation Manager
• Mediator Dispatcher
• Notification Handler
• Network Element Access Control
• Credential Library
• Mediation using SNMP