Head of Software Engineering

Tampa
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist – GenAI & AI Engineering

Lead Software Engineer - MLOps Platform

Junior Data Scientist / Data Analyst

Data Scientist

Head of Data Science

Head of Machine Learning (Recommendations, AI Stylist & Search)

We're looking for a dynamic and hands-on Head of Software Engineering to lead our development team and help scale our platform. If you are passionate about clean tech, thrive in a fast-paced startup environment, and love building scalable software solutions, this could be the perfect role for you.

We're a fast-growing SaaS startup at the forefront of the green energy revolution. Our mission is to develop cutting-edge technology that accelerates the global transition to renewable energy, empowering businesses and consumers to reduce their carbon footprint. Based in Tampa, we're a tight-knit team passionate about innovation and sustainability.

Responsibilities:

Lead, mentor, and grow a team of software engineers to deliver high-quality products on time.
Oversee the entire software development lifecycle, from planning and architecture to deployment and ongoing maintenance.
Collaborate closely with the product, operations, and business teams to align technical efforts with business goals.
Drive the adoption of best practices in coding, testing, and architecture, with a focus on scalability and performance.
Stay ahead of industry trends, particularly in renewable energy and software engineering, and make recommendations for improving our tech stack and processes.
Lead by example through hands-on development, especially in areas involving Python, JavaScript, React, and AWS.
Manage cloud infrastructure and ensure the security, reliability, and scalability of our platform.Required Skills & Experience:

7+ years of experience in software development, with at least 3+ years in a leadership or management role.
Strong proficiency in Python, JavaScript, React, and AWS services.
Experience building SaaS products and scaling cloud-based platforms.
Proven experience leading teams through all phases of the software development lifecycle.
Strong understanding of microservices, API development, and modern DevOps practices.
Ability to translate business goals into effective technical strategies.
Experience working in startups or small teams, with a "roll up your sleeves" mentality.
Passion for renewable energy, sustainability, and making a positive impact on the world.Nice-to-Have:

Experience with CI/CD pipelines and containerization technologies like Docker.
Familiarity with AI, machine learning, or data-driven platforms.
Knowledge of energy markets, renewable energy technologies, or carbon tracking solutions.Why Join Us:

Be part of a mission-driven company committed to making the world more sustainable.
Work in an environment that encourages innovation, autonomy, and creative problem-solving.
Up to $250,000 per annum, 10% annual performance based bonus, Private healthcare, 401k and stock/share options
Flexible working hours and remote work opportunities.
Opportunity to lead and shape a growing team in an exciting, high-impact sector.How to Apply: Please send your resume and a brief cover letter detailing your experience and interest in the role to or call (phone number removed)

Join us in driving the renewable energy revolution! 🌍⚡

Spectrum IT Recruitment (South) Limited is acting as an Employment Agency in relation to this vacancy

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.