Artificial Intelligence Engineer
thrivelyBrooklyn (NY)
About the role
Senior AI Engineer Williamsburg, NY
About the Opportunity:
Thrively is partnering with an innovative, fast-growing technology company that is transforming how small businesses operate through AI-powered products and automation. Our client is looking for a Senior AI Engineer to help architect and scale next-generation AI capabilities across their platform. This is a high-impact opportunity to join a collaborative and product-driven engineering team where your work will directly influence the customer experience, product roadmap, and overall company growth trajectory. You’ll work closely with Engineering, Product, and Design leadership to build intelligent systems and AI-powered experiences used in real-world production environments.
What You’ll Be Doing:
• Build AI-powered agent and chat capabilities that help customers operate and grow their businesses more efficiently• Design and deploy scalable AI infrastructure and pipelines supporting real-time interactions in production• Develop and optimize Retrieval Augmented Generation (RAG) workflows, vector embeddings, and vector database integrations• Prototype, evaluate, and iterate on AI features using customer feedback and performance data• Partner cross-functionally with Product, Design, and Engineering leadership on strategic product initiatives• Contribute to architecture decisions, experimentation frameworks, and AI evaluation methodologies• Help establish best practices around MLOps, deployment, monitoring, observability, and model evaluation
What We’re Looking For:
• 5+ years of experience in AI, Machine Learning, NLP, or related engineering environments• Strong Python development experience, ideally within modern web application environments• Experience working with frameworks and technologies such as Django, React, and PostgreSQL• Hands-on experience building and deploying AI-powered applications into production environments• Deep familiarity with LLM ecosystems, prompt engineering, evaluation workflows, and fine-tuning strategies• Experience leveraging OpenAI, Anthropic, or similar AI APIs in production use cases• Experience with agentic AI frameworks such as Lang Chain, Lang Graph, Pydantic AI, or similar technologies• Experience implementing RAG architectures, vector embeddings, and vector databases• Familiarity with end-to-end MLOps practices including deployment, monitoring, experimentation, and evaluation• Experience operating within Agile product and engineering teams What Makes Someone Successful Here:• Strong problem-solving instincts in fast-moving and ambiguous environments• Ability to make thoughtful decisions with incomplete information• Genuine curiosity around how systems work under the hood• Excellent communication and collaboration skills• Team-first mindset with low ego and high ownership• Passion for building products that create meaningful customer impact What Our Client Offers:• Competitive compensation package• Comprehensive Medical, Dental, and Vision coverage• 401(k) program• Flexible PTO and company holidays• Wellness and fitness benefits• Hybrid work environment in Boston• Opportunity to help shape and scale AI capabilities at a rapidly growing company• High ownership, visibility, and impact on both product and engineering direction If you enjoy building AI systems in fast-paced startup environments and want to help shape the future of AI-powered products, we’d love to connect.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
More like this
