Senior Engineering Manager — Data & AI ML Platform

A.P. Moller - Maersk; Bengaluru; Hybrid; INR 1,800,000 - 2,400,000; Full time

Benefits offered by this job

Flexible working hours

International exposure

Job summary

Maersk seeks an experienced senior engineering leader to head a multi-squad group across four domains: Commercial AI, Asset Intelligence, Data & AI Platform, and Architecture & Scale. You will sit in India and Europe, driving AI-native product development that directly improves terminal performance and revenue.

You will coach engineers, shape architecture, and deliver production-grade solutions at scale, balancing commercial impact with engineering excellence in a hybrid setup.

Qualifications

• 14+ years in software/data/ML engineering, with leadership of multi-team groups.
• Proven delivery in production, at scale, with business impact.
• Experience shipping LLM-powered products and AI-native workflows.

Responsibilities

• Lead a multi-squad engineering group spanning four domains (Commercial AI, Asset Intelligence, Data & AI Platform, Architecture & Scale).
• Coach squad leads, review architectures, and drive delivery to terminals.
• Ensure cloud data platform reliability, cost-efficiency, and observability.
• Bridge engineering work with commercial and asset outcomes across global terminals.

Skills

Engineering leadership

Player-coach credibility

Data platform depth

Gen AI in production

Commercial & asset instinct

People leadership

Decision speed

Tools

AWS data platform (S3, Glue, EMR, Redshift, SageMaker, Bedrock)

Job description

Who We Are

APM Terminals operates one of the world’s largest port and terminal networks. Inside it, our Digital, Data & AI Engineering organization is building something rare in this industry: AI-native engineering squads whose work directly changes how terminals run — vessels turning faster, equipment lasting longer, revenue growing. Our purpose is simple: make every terminal the best version of itself.

You will lead a multi-squad engineering group of ~25 engineers spanning four domains: Commercial AI, Asset Intelligence, Data & AI Platform, and Architecture & Scale. Your teams sit in India and Europe. Your customers are commercial leaders, asset managers, and terminal operators worldwide.

What You Will Own

Commercial AI

Generative AI products for commercial teams — market intelligence, pricing and revenue intelligence, and contract analytics. LLM-powered co-pilots and agentic workflows that help commercial teams price sharper and win more.

Asset Intelligence

AI for the physical backbone of the business — total cost of ownership modeling, asset replacement and lifecycle planning, simulation, and the data foundation for asset management across a multi-billion-dollar equipment fleet.

Data & AI Platform

The AWS-native data platform every product is built on — enterprise data lake, large-scale cloud migration, data engineering, ML Ops, AI Ops, and observability. Reliable, governed, and cheap to build on.

Architecture & Scale

The architecture standards, scaling patterns, and engineering practices that let one terminal’s solution become a network-wide capability — designed for the tenth consumer, not the first.

How We Work — Our Operating Principles

• Player-coach leadership. You and your squad leads build alongside the teams — writing code, reviewing models, shipping to terminals. When the person making decisions is also in the work, things move faster and outcomes get better.

• Outcomes over technology delivery. Every engineer knows what changes at the terminal because of their work. Not sprints closed, not models deployed — vessels turning faster, revenue growing.

• Every engineer is a force multiplier. AI handles the repetitive work so people spend their time on decisions that drive commercial and terminal outcomes. The multiplier isn’t fewer people — it’s people solving bigger problems.

• Forward-deployed engineering. We build where the problem lives — embedded with planners and operators, feeding every terminal’s fix back into the platform so it becomes a capability for the whole network.

What Success Looks Like in Your First Year

• Commercial AI products in the hands of commercial teams and moving revenue — with measured adoption, not just deployment.

• The cloud migration of our core data platform completed with improved reliability and lower run cost.

• Asset intelligence models informing real replacement and investment decisions, with finance and operations trusting the numbers.

• Four squad leads operating as genuine player-coaches — growing, accountable, and capable of running the engine when you step back.

• An engineering culture where AI-assisted development is the default and delivery speed is visibly compounding.

What You Bring

• Engineering leadership at scale. 14+ years in software/data/ML engineering, 5+ years leading multi-team organizations (25–50 engineers) through senior leads — with a track record of delivery in production, at scale, where the business depended on it.

• Player-coach credibility. You still build. You can review an architecture, challenge a model design, or pair on a hard problem — and your teams know it. You coach squad leads to do the same.

• Data platform depth. Hands‑on history with modern cloud data platforms (AWS preferred — S3, Glue, EMR, Redshift, SageMaker, Bedrock or equivalents), large‑scale migrations, data engineering, ML Ops and AI Ops, and platform observability.

• Gen AI in production. You have shipped LLM‑powered products — RAG systems, co‑pilots, or agentic workflows — where quality, latency, cost, and evaluation were real engineering constraints, not demos.

• Commercial and asset instinct. You connect engineering to money. Pricing, revenue intelligence, TCO modeling, lifecycle economics — you understand the decision your product enables, and you push back on poorly framed requirements.

• People leadership that compounds. You hire well, grow leaders beneath you, have honest conversations early, and build teams that outlast you. You lead distributed teams across time zones with clarity and care.

• Decision speed under ambiguity. You make the call, communicate it clearly, and keep multiple workstreams moving. Momentum over consensus‑seeking.

Nice to Have

Terminal operations, port logistics, shipping, or adjacent supply chain domains AI‑native development tooling rolled out as engineered team workflows (Claude Code, Cursor, Copilot or similar) FinOps for data and AI workloads Experience presenting to C‑level stakeholders.

What We Offer

A senior leadership role with genuine scope: four squads, a global platform, and products that move measurable revenue and cost in one of the world’s largest terminal networks. High ownership, direct access to senior leadership, international exposure across our global network, and the backing to build an AI‑native engineering organization the industry will benchmark against. Flexible working within a collaborative hybrid model.

We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, please contact us by emailing [e-mail].

Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.