AI Engineer

Pay Rate: $50-60/hr

This is a high-visibility, high-impact opportunity to join a small, elite team driving Agentic AI innovation within one of the largest data ecosystems in the world. As part of this team, you will report directly to engineering leadership on a dedicated initiative focused on accelerating enterprise use cases through Agentic AI - including legacy code modernization, data pipeline optimization, and workflow automation.

The team has already proven out early success and is now expanding to deliver additional pilots. This is intentionally a lean, two-person engineering team designed to move fast and stay nimble. You’ll have direct ownership over meaningful work and the autonomy to drive real outcomes.

What You’ll Do

• Design, build, and deploy AI agents and agentic workflows to automate and accelerate enterprise processes across code modernization, data pipelines, and operational workflows

• Engineer RAG (Retrieval-Augmented Generation) pipelines to ground LLMs in domain-specific enterprise data for accurate, context-aware outputs

• Develop and iterate on LLM-powered tools and automation using frameworks like LangChain, HuggingFace, and similar agentic AI tooling

• Optimize and modernize data pipelines and SQL-based systems for performance and scalability

• Collaborate directly with IT leadership and cross-functional stakeholders (product, analytics, business) to translate ambiguous problems into working solutions

• Operate with a bias toward action - move quickly from idea to execution in a fast-paced, pilot-driven environment

• Contribute to the broader AI strategy by proving out new use cases and building reusable patterns for the enterprise

What We’re Really Looking For (Intangibles > Existing Knowledge)

The hiring manager has emphasized that fast learner takes priority over existing knowledge and is looking for the following intangibles above all:

• Exceptional raw intellect & learning velocity - demonstrated ability to quickly absorb new domains, synthesize information, and operate with limited guidance

• Elite problem-solving ability - breaks down ambiguous problems, forms hypotheses, and iterates toward solutions with rigor and creativity

• High curiosity & ownership mindset - proactively explores “why” and “what’s next,” not just “what’s assigned”

• Evidence of innovation - history of building, experimenting, or improving systems (side projects, startups, open-source contributions, academic research)

• Bias toward action - moves quickly from idea to execution; comfortable operating in ambiguity and imperfect conditions

• Strong communication skills - can articulate complex ideas clearly to both technical and non-technical stakeholders

• Leadership potential - demonstrates initiative, influence, and the ability to elevate others even without formal authority

• Cultural fit: low ego, high accountability - collaborates well, takes responsibility for outcomes, and prioritizes team success over individual credit

Why This Opportunity

• High-impact ownership - This role sits close to critical data products and infrastructure that directly influence business decisions and operational outcomes across one of the largest data ecosystems in the world

• Modern engineering culture - The team is leaning into automation, AI-assisted development, and emerging agentic workflows to improve engineering speed and quality

• Ownership with autonomy - This isn’t a ticket-taking role. Engineers drive design decisions, influence roadmaps, and partner directly with stakeholders

• Cross-functional visibility - Collaborate closely with product, analytics, and business teams for broad organizational exposure

• BS or MS in Computer Science, Engineering, Data Science, or related field from a strong academic program

• Python as primary language - proficiency with AI/ML libraries (PyTorch, HuggingFace Transformers, Scikit-learn, Pandas, NumPy)

• Hands-on experience with LLMs (e.g., GPT, Gemini, Flan-T5, LLaMA, etc.)

• Strong SQL skills and experience working with large-scale data (optimization, schema design, pipeline development)

• Familiarity with cloud platforms (GCP preferred but not a deal-breaker; AWS/Azure acceptable)

• Version control proficiency (Git/GitHub) * Open-source contributions or a strong GitHub portfolio

• Teaching assistant experience (demonstrates communication + mentorship ability)