Senior AI Engineer

ZipRecruiter
Wakefield
1 month ago
Applications closed

Related Jobs

View all jobs

Principal Data Scientist - NLP

Senior Big Data Engineer - AI Forecasting

Senior Data Engineer with ML knowledge

Senior Data Engineer

Senior Data Engineer

Senior Electronics Engineer

Job Description

Senior AI Engineer: C-4 Analytics

C-4 Analytics is a fast-growing, private, full-service digital marketing company that excels at helping automotive dealerships increase sales, increase market share, and lower cost per acquisition. We are currently hiring for a Senior AI Engineer as we look to expand our team and support our growing roster of local clients.

Who We're Looking For: Senior AI Engineer - Remote

We are seeking an AI Wizard who speaks fluent LLM and dreams in Vector Databases. As a Senior AI Engineer, you will be working with the latest in AI technology, including agent libraries, advanced LLMs, and NLP tools. You'll have the opportunity and autonomy to lead the development and implementation of AI-powered solutions. This role will focus on integrating diverse data sources, refining AI interactions through prompt engineering, and collaborating with cross-functional teams to drive artificial intelligence adoption and innovation. Your work will directly impact how automotive dealerships operate and compete in their markets.

If you've ever wanted to:

  • Be the person who makes AI actually useful (not just another chatbot that tells jokes)
  • Work with cutting-edge tech without the "we're changing the world with blockchain" nonsense
  • Build systems that impact real businesses and real people
  • Never have to explain to your family why you're "still playing with computers" (because the results speak for themselves)

A day in the life of a Senior AI Integration Engineer:

  • Working with NLP that utilizes cutting-edge AI technologies to integrate AI-driven insights across company systems, enhancing access to data and supporting decision-making processes.
  • Leverage AI technologies (LLMs) to continue development and implement chatbot agents for company-wide insights.
  • Implement test-driven prompt engineering to design, optimize, and refine prompts for accurate and relevant AI-driven interactions.
  • Integrate AI with internal and external data sources, ensuring seamless access to business-critical data.
  • Collaborate with engineering, data science, product management, and operations teams.
  • Assist in data architecture, preparation, and sanitization for effective use by AI models.
  • Develop AI strategies aligned with business goals and objectives.
  • Monitor and optimize AI performance for continuous improvement.
  • Advise on AI adoption and identify areas for efficiency and innovation.
  • Ensure ethical use of AI, maintaining data security, privacy, and compliance.
  • Stay current with advancements in AI, ML, and LLM technologies.

The Tech Toybox includes:

  • Modern AI Frameworks | Advanced LLMs & NLP tools
  • TensorFlow/PyTorch for those deep learning dreams
  • Cloud platforms to make it all float
  • Langchain & LlamaIndex for connecting the dots

What you’ll need to succeed:

  • At least 3 years of proficiency in AI and machine learning technologies, particularly LLMs.
  • Strong experience with prompt engineering and NLP tasks.
  • Proven experience integrating AI systems with data platforms (databases, data lakes, APIs).
  • Familiarity with data wrangling and preparation tools.
  • Programming skills in Python and experience with AI frameworks (TensorFlow and PyTorch).
  • Experience with cloud platforms (AWS, Google Cloud, etc).
  • 3+ years of professional experience working in agile teams and SDLC for AI projects.
  • Knowledge of LangChain, LangGraph, LlamaIndex, Vector Databases (i.e., OpenSearch, ElasticSearch), RAG, ETL.

This role requires a blend of technical expertise, strategic thinking, and collaborative skills to effectively integrate AI solutions and drive business value.

Flexibility:

The Senior AI Engineer may benefit from the flexibility to work in a way that suits them best. We offer the following working options:

  • Office-Based: Our modern and well-equipped office space provides a collaborative environment where you can work closely with teams.
  • Remote: We support remote work arrangements, allowing you to work from the comfort of your own home.
  • Hybrid: For those who prefer a balance between office and remote work, we offer a hybrid model.

Compensation:

We offer a competitive compensation commensurate with experience and qualifications. The starting annual on-target earning for this position is $150,000.00. The final salary will be determined based on factors such as skills, knowledge, and demonstrated expertise.

Please note that the stated salary range is flexible and negotiable based on individual qualifications and fit for the role.

Working at C-4 Analytics

We provide our employees with a range of benefits, including career development programs, unlimited paid time off, and additional perks. All are welcome to visit our careers and culture page for more details.

More About C-4 Analytics

C-4 Analytics takes the guesswork out of advertising. We provide real value to our clients because we value them as partners. We are results-driven and our strategies drive results.

Powered by JazzHR

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

Data Science Jobs in the Public Sector: Exploring Opportunities Across GDS, NHS, MOD, and More

Data science has emerged as one of the most influential fields in the 21st century, transforming how organisations make decisions, improve services, and solve complex problems. Nowhere is this impact more visible than in the UK public sector. From the Government Digital Service (GDS) to the National Health Service (NHS) and the Ministry of Defence (MOD), government departments and agencies handle vast amounts of data daily to support the well-being and security of citizens. For data enthusiasts looking to make a meaningful contribution, data science jobs in the public sector can offer rewarding roles that blend innovation, large-scale impact, and societal benefit. In this comprehensive guide, we’ll explore why data science is so pivotal to government, the roles you might find, the skills needed, salary expectations, and tips on how to succeed in a public sector data science career.

Contract vs Permanent Data Science Jobs: Which Pays Better in 2025?

Data science sits at the intersection of statistics, machine learning, and domain expertise, driving crucial business decisions in almost every sector. As UK organisations leverage AI for predictive analytics, customer insights, and automation, data scientists have become some of the most in-demand professionals in the tech job market. By 2025, data scientists with expertise in deep learning, natural language processing (NLP), and MLOps are commanding top-tier compensation packages. However, deciding whether to become a day‑rate contractor, a fixed-term contract (FTC) employee, or a permanent member of an organisation can be challenging. Each path offers a unique blend of earning potential, career progression, and work–life balance. This guide will walk you through the UK data science job market in 2025, examine the differences between these three employment models, present sample take‑home pay scenarios, and offer strategic considerations to help you determine the best fit for your career.