Head of Software Engineering, DevOps, & AI

WHAT YOU’LL DO

Seakeeper is revolutionizing the marine industry through cutting-edge technologies in a fast-moving, innovation-driven organization. As our Director of Software Engineering, DevOps & AI, you'll lead the development of the cloud platform, building the infrastructure, engineering practices, and AI capabilities that power the next generation of the Seakeeper experience. You'll partner closely with leaders across Engineering, Product, Manufacturing, and Business Technology to deliver scalable platforms, accelerate digital innovation, and transform data into business value. You'll make an immediate impact across Seakeeper by:

Software Engineering

Leading a team of software engineers responsible for platform services, APIs, and internal business solutions.

Providing technical direction, architectural oversight, and engineering standards across all software initiatives

Driving effective planning, prioritization, and execution through modern software development practices.

Recruiting, developing, and mentoring engineering talent while building a culture of accountability, collaboration, and continuous improvement

Balancing strategic leadership with hands-on engagement in architecture, design reviews, and technical decision-making

DevOps

Establishing and maturing DevOps practices across Business Technology, including CI/CD, infrastructure-as-code, monitoring, and incident management

Defining release governance, deployment standards, testing disciplines, and operational best practices

Partnering with Engineering to align development, security, and deployment processes

Building and leading a high-performing DevOps capability that improves speed, stability, and reliability

Tracking and improving key platform performance metrics, including uptime, deployment frequency, and recovery times

Cloud Architecture & Connected Product Platform

Establishing the platform's security, networking, identity, and trust architecture in partnership with Embedded Systems Engineering

Ensuring scalability, reliability, and maintainability as the connected fleet and product portfolio grow

Evaluating technology solutions and vendors, making strategic build-versus-buy recommendations

Applied AI & Machine Learning

Leading the identification and delivery of AI and machine learning solutions that improve products, operations, quality, and customer outcomes

Developing predictive and prescriptive analytics capabilities using manufacturing, and enterprise data

Establishing AI/ML development, deployment, governance, and lifecycle management practices

Partnering with business and functional leaders to prioritize high-value automation and intelligence initiatives

Driving the practical adoption of AI technologies that create measurable business impact across the organization

WHAT YOU NEED TO SUCCEED

Do you have a positive attitude, an eagerness to learn, and the ability to hustle in a fast-paced environment? Then Seakeeper is the place for you! Here are a few other specifics you’ll need to have to succeed.

MUST-HAVES

Bachelor’s degree in computer science, software engineering, electrical engineering, or a related technical field required.

Experience working in business systems, IT, or technology leadership role with 10+ years of progressive experience including:

Cloud architecture or platform engineering, with production experience on Microsoft Azure

Hands-on experience with Container Apps, Azure Kubernetes Service (AKS) or equivalent container orchestration, PostgreSQL or similar relational databases, Blob Storage, Key Vault, and Entra ID

Direct experience shipping OTA or firmware-update infrastructure for a physical connected product – automotive, marine, industrial IoT, medical device, or similar

Infrastructure-as-code experience with Terraform

Networking fundamentals — virtual network design (hub-and-spoke topology), VPN Gateway, TLS/mTLS, DNS, and load balancing

Experience designing microservices architectures, RESTful APIs, and event-driven integration patterns

Hands-on DevOps practice: CI/CD pipeline design and implementation (Azure DevOps or GitHub Actions

Containerization and orchestration experience (Docker, Kubernetes)

A dynamic leader who understands the value of being present, accessible and accountable to their team and the business stakeholders

Observability tooling — Azure Monitor, Log Analytics, and Application Insights, or equivalent platforms (Datadog, Grafana/Prometheus)

Experience with progressive delivery patterns — canary releases, blue-green deployments, feature flags, and automated rollback

Applied AI/ML experience with real technical depth — Python and standard frameworks (PyTorch, scikit-learn, or similar)

Demonstrated experience building custom ML models from the ground up for process-improvement or operational use cases — not limited to configuring pre-built APIs or AutoML platforms

MLOps practice — model versioning, deployment, and monitoring in production (MLflow, Azure Machine Learning, or equivalent)

Data pipeline and ETL/ELT experience (Azure Data Factory, dbt, or equivalent)

Experience with time-series data and predictive maintenance or anomaly-detection modeling is highly relevant given the telemetry use case

Security and PKI experience — certificate lifecycles, code-signing chains, and trust architecture. This role owns the signing chain for every firmware update that reaches the fleet, not a delegated afterthought

Secrets management experience (Azure Key Vault or HashiCorp Vault)

People-management – you've directly managed engineers before, including hiring, code review, and career development

Managing budgets & external vendor relationships

Familiarity with the following:

IoT/embedded security threat models and mitigations

Data warehousing concepts and tooling (Azure Synapse, Snowflake, or similar)

SRE practices — SLOs/SLIs, error budgets, on-call rotations, and incident management

Comfortable operating at the executive level — this role feeds directly into quarterly technology reviews with the CEO, CFO, and CTO, and needs to translate technical tradeoffs into business terms

Comfortable being the architect and the builder at once — this is a small, growing team, not one with a bench to hand things off to

Track record partnering directly with embedded or firmware engineering teams across the device-to-cloud boundary.

Excellent communication, stakeholder management, and strategic planning skills

Flexible and adaptable with the ability to deal with ambiguity and triaging competing priorities

Openness to collaboration in all scenarios – you bring good ideas to the table, but can also recognize them from others

Flexible and agile with the ability to pivot quickly to changing circumstances and business demands

Changemaker with a bias for positive action

NICE-TO-HAVES

Master’s degree in computer science, data science, or a related field preferred

Relevant industry certifications preferred – Microsoft Certified: Azure Solutions Architect Expert, Azure AI Engineer Associate, Certified Kubernetes Administrator (CKA), or equivalent

Infrastructure-as-code experience with Bicep or ARM templates

Experience in marine, automotive, or industrial equipment connected-product platforms

Prior experience standing up DevOps practice from scratch at a growth-stage or PE-owned manufacturing company

Experience managing external technology vendors and evaluating build-vs-buy tradeoffs on live platform decisions

Contribution to open-source tooling in the DevOps, MLOps, or IoT space

Experience operating in a multi-site or distributed manufacturing environment

MORE DETAILS YOU'LL WANT TO KNOW

This is a new role that you will have the opportunity to pioneer and make an immediate impact

This is an onsite position, based in either our Leesport, PA, or Ft. Myers, FL, locations

Up