Senior Software Engineer, Network Operational Intelligence

Senior Software Engineer, Network Operational Intelligence(Maersk)

Job Level 4 (Senior Software Engineer)

This position will be based in Bangalore

A.P. Moller - Maersk

A.P. Moller – Maersk is the global leader in container shipping services. The business operates in 130 countries and employs c. 80,000 staff. An integrated container logistics company, Maersk aims to connect and simplify its customers’ supply chains.

We Offer

Joining Maersk will embark you on a transformational journey with great opportunities for career development within a global organization. As a Senior Software Engineer, you will design, engineer and run our capabilities for the Network Automation and Orchestration Tools stack for network and perimeter products and platforms that enable highly distributed global business for site, fleet, asset and IoT connectivity, required to deliver against our strategy. You will be exposed to a wide and challenging range of needs and opportunities requiring you to engage closely with stakeholders across all levels within Maersk as you mature and evolve our Ops Intelligence capabilities for Network Ops Intelligence to become world class.

The Brief

A globally focused shipping and transportation organisation is continuing to drive an ambitious and complex change and transformational programme to deliver a service of excellence for its customers and clients worldwide. The Global CTIO has a mandate from the Maersk board to lead the Technology transformation of Maersk which will enable the Maersk business strategy to become the global integrator of container logistics through digitising the Maersk business processes and customer engagement.

The Technology Function is fundamental to enable the company’s transformation and in response to this demand, our in-house technological capability is growing exponentially. We are recruiting world class talent to ensure that the technology services are modernised to enable Maersk to become a logistics integrator leveraging a competitive advantage through technology.

Why this job matters?

The Network Ops Intelligence Engineering function is essential to our transformation, it is a central team within Network Architecture & Engineering, responsible for the delivery of product roadmaps, technical vision and quality across Fulfilment and Assurance that underpin our network and perimeter capabilities and products.

Reporting to the Senior Network Ops Intelligence Engineering Manager you will serve as a Senior Software Engineer, ensuring that our systems and tools for the network Ops Intelligence realise business value. Your role is responsible for technical design and delivery of solutions across the network Ops Intelligence applications landscape from Planning to analytics driven AIOps. All built to industry leading standards and running seamlessly across various cloud and on-prem platforms, allowing frictionless and seamless operations of our network and perimeter platforms.

Scope

The Network Ops Intelligence team at Maersk is responsible for enabling, automating, and enhancing the management of data networks across Core, Edge, and Cloud locations (offices, warehouses, terminals, vessels, data centres, cloud environments, etc.), and is expanding into AI-driven network operations — building intelligent, autonomous systems for observability, assurance, and decision-making.

This role sits at the intersection of deep software engineering and applied AI : designing and building production-grade platforms and tools, and infusing them with Generative AI, Large Language Models (LLMs), and agentic frameworks to transform how networks are operated.

Key areas include but are not limited to:

• •Automation & Orchestration: Design and implementation of workflows and systems to automate provisioning, configuration, monitoring, and assurance of network services.
• •AI-Augmented Operations: Develop agentic AI solutions using LLMs, orchestration frameworks and vector stores to enable intelligent automation, natural language interfaces, and autonomous troubleshooting.
• •Tooling & Platform Development: Build scalable internal tools for network inventory, monitoring, telemetry collection, event correlation, and intent-based management.
• •Intelligent Observability & Insights: Use GenAI to augment monitoring and assurance — alert summarization, root cause inference, change impact prediction, and knowledge extraction from telemetry, syslogs, traps, and alarms.
• •Prompt Engineering & Reasoning: Design structured/dynamic prompts, chains, and Retrieval-Augmented Generation (RAG) workflows for context-aware insights from large-scale network data.

Our mission is to drive network intelligence, automation, and operational excellence by bridging infrastructure with software and AI — building LLM-based platforms that are autonomous, explainable, and user-friendly.

Specific Job Requirements

We are looking for a Senior Software Engineer (8+ years) with a product mindset — a strong software engineering foundation combined with hands-on applied AI/LLM engineering experience. The role holder will demonstrate deep expertise in Python-based platform development and in building LLM-powered systems for production use.

Software Engineering Expertise

• •Advanced Python proficiency: Mastery of Python syntax, data structures, OOP principles, and AI/NLP libraries (LangChain, LangGraph, Transformers, OpenAI SDK, HuggingFace, LlamaIndex).
• •Web frameworks: Hands-on expertise with FastAPI, Flask, or Django for backend service development; ability to lead projects and mentor developers.
• •API development leadership: Design and development of secure, high-performance RESTful APIs, with strong understanding of authentication mechanisms and integration patterns.
• •Databases & ORM: In-depth experience with relational databases (PostgreSQL, MySQL, SQLite) and ORM frameworks (SQLAlchemy, Django ORM).
• •Microservices & Docker: Architecting modular, scalable, resilient microservices-based systems with containerization.
• •CI/CD & DevOps: GitHub workflows, Jenkins, automated build/test/deploy pipelines.
• •Testing & quality: TDD discipline with PyTest/unittest; strong focus on code quality, maintainability, and reproducibility.
• •Algorithms & problem-solving: Design, analysis, and optimization of algorithms; strategic problem-solving for complex challenges.

AI & Agentic Engineering Expertise

• •Hands-on LLM experience: Building applications with foundation models (OpenAI, Claude, LLaMA, Mistral, Gemini) via APIs and self-hosted/open-weight models.
• •Agentic AI systems: Designing autonomous/semi-autonomous agents with multi-step reasoning, tool/function calling, planning, memory, and state management — using LangGraph, LangChain, or similar frameworks (e.g., AutoGen, CrewAI, Semantic Kernel, Model Context Protocol (MCP) for tool integration).
• •Prompt engineering & RAG: Structured prompts, few-shot and chain-of-thought techniques, embedding models, vector stores (FAISS, Chroma, Weaviate, pgvector), hybrid search, chunking strategies, and re-ranking for retrieval pipelines.
• •LLMOps & evaluation: Systematic evaluation of LLM outputs — golden datasets, LLM-as-judge, regression testing of prompts/chains; observability and tracing of agent workflows (e.g., LangSmith, Langfuse, OpenTelemetry for GenAI); handling hallucination mitigation, fallback mechanisms, and graceful degradation.
• •Fine-tuning & model adaptation : Familiarity with parameter-efficient fine-tuning (LoRA/PEFT), instruction tuning, and when to choose fine-tuning vs. RAG vs. prompting.
• •Structured outputs & tool integration : Function calling, JSON-schema-constrained generation, and integrating LLMs securely with APIs, databases, and monitoring platforms.
• •MLOps & inference infrastructure: Containerized AI workloads, GPU orchestration, batch vs. streaming inference, model serving (e.g., vLLM, Triton), token/cost optimization, caching, and rate limiting.
• •AI security & governance : Data pri