Ai Engineer Jobs

About The Position

Requirements

• 3-5+ years of experience in a hands-on technical role such as software engineering, data science, or machine learning engineering.
• Deep, hands-on experience with LLMs and AI agents as well as core machine learning concepts (both supervised and unsupervised), natural language processing (NLP), and data modeling.
• Demonstrated ability to understand business challenges and translate them into technical requirements and solutions.
• Exceptional interpersonal and communication skills, with the ability to articulate complex technical concepts to a non-technical audience.
• A proactive and analytical approach to problem-solving, with a track record of delivering innovative solutions.

Nice To Haves

• Prior experience in a "forward deployed," consulting, or client-facing technical role is highly desirable.
• Hands-on experience with major cloud platforms (AWS, Google Cloud, Azure) and their associated AI/ML services (e.g., SageMaker, Vertex AI, Azure ML).
• Familiarity with data engineering principles, including ETL/ELT processes, data warehousing, and working with large datasets.
• Knowledge of a specific business domain such as payments, finance and operations in financial services firms.

Responsibilities

• Collaborate & Analyze: Work closely with business stakeholders to conduct in-depth analyses of existing business processes, workflows, and pain points. Identify and prioritize opportunities where AI can deliver maximum impact.
• Solution Design & Prototyping: Design and rapidly prototype innovative AI-powered solutions. This includes developing proof-of-concepts (POCs) and where appropriate, minimum viable products (MVPs) to demonstrate feasibility and value.
• Bridge Communication Gaps: Serve as a key technical translator and liaison between non-technical business users and core engineering teams, ensuring requirements are clearly understood and solutions are fit-for-purpose.
• Stay Current: Maintain a deep understanding of the rapidly evolving AI landscape, including new tools, techniques, and best practices in machine learning, natural language processing, and generative AI.
• Measure & Optimize: Define key performance indicators (KPIs) to measure the effectiveness and ROI of AI initiatives.
• Documentation & Training: Participate in the creation of comprehensive documentation for new AI-driven processes and provide training and support to business users to ensure successful adoption.

Benefits

• medical, dental & vision coverage
• 401(k)
• life, accident, and disability insurance
• wellness programs
• paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays