Senior AI Engineer

Title: Senior AI Engineer

Location: Portland OR US

Type: Full-time

Workplace: Fully remote

Job Description:

Ascend is a fast-growing SaaS company that automates invoice processing and payments for mid- and large enterprise customers. Our flagship product, Ascend AP, leverages AI, powerful real-time ERP integrations, and embedded payments technology to save our customers tens of millions of dollars every year. Our customers include household names like NASCAR, Panera Bread, Virgin Voyages, and PGA TOUR as well as many of the nation's largest and most renowned hospitals and health systems, financial services providers, and higher ed institutions.

 

Ascend is a fully remote company that offers competitive pay, exceptional benefits including unparalleled 401(k) matching, and unlimited time off. Most importantly, we offer the chance to learn, take ownership, and grow in your career the way you've envisioned.

 

What would you do at Ascend?

As a Senior AI Architect at Ascend, you will lead our strategy and execution for applying Generative AI, LLMs, and advanced ML techniques to high-impact business problems across the invoice automation and payments lifecycle. You will work cross-functionally with engineering, product, and business stakeholders to design and implement scalable, compliant, and highly effective AI solutions-bringing cutting-edge innovation into real-world Accounts Payable workflows. You will serve as both a technical expert and strategic thought leader, helping Ascend push the boundaries of what's possible with Gen AI while delivering measurable business value.

 

Your day-to-day would include:

• Leading the design, development, and deployment of sophisticated AI/ML models, especially LLMs and multi-agent Gen AI architectures.

• Collaborating with business stakeholders to identify high-impact AI use cases and propose innovative solutions.

• Training and fine-tuning foundation models using techniques such as transfer learning, self-supervised learning, and domain adaptation.

• Building, scaling, and optimizing AI workloads and infrastructure using cloud-native technologies like Kubernetes, Argo, and TensorFlow.

• Driving the development of AI solutions that meet enterprise governance, security, and compliance standards.

• Partnering with Product Management to define the Gen AI roadmap and lead delivery teams to successful outcomes.

• Coaching and mentoring a distributed AI engineering team and fostering a deep AI culture across the organization.

• Justifying the value and ROI of AI solutions through rigorous methodology, estimation, and measurement.

• Creating technical documentation and capturing IP for long-term reusability and scalability.

• Collaborating with academic and industry partners to stay at the forefront of AI innovation and translate trends into strategic opportunities.

Requirements

• Proven experience in developing and deploying Gen AI and LLM-based solutions in enterprise settings.

• Deep understanding of modern AI/ML architecture, with a focus on generative models and multimodal learning.

• Strong software engineering skills, particularly around ML infrastructure and backend services.

• 5+ years in machine learning engineering, with at least 2 years focused on LLM-based or GenAI production deployments and monitoring, with at least 2 years building solutions for large-scale AI applications.

• Demonstrated ability to evaluate, experiment with, and implement emerging algorithms and modeling techniques.

• You must be proficient with at least three of the following:

• PyTorch, HuggingFace Transformers, LangChain

• Retrieval-augmented generation (RAG) and vector DBs (e.g., Pinecone, Weaviate, FAISS)

• Prompt engineering & system message chaining with OpenAI or Claude APIs

• Containerized model deployment (Docker, Argo, Kubernetes)

• Fine-tuning methods: LoRA, QLoRA, PEFT, or parameter-efficient training

• Cloud-native AI toolchains (e.g., AWS Sagemaker, Bedrock, GCP Vertex AI)

• Exceptional communication and collaboration skills; ability to work across business and technical teams.

• Bachelor's degree in Computer Science or related field preferred.

Benefits

We offer everything you'd expect from a profitable company including a great salary, comprehensive health care benefits (100% covered for employees, 50% for dependents), and a generous retirement plan match.

• You'll receive an annual Lifelong Learning & Wellness Allowance to use towards learning opportunities of your choice (cooking lessons, dance lessons, language lessons, etc.) or to achieve your health and wellness goals.

• You'll receive flexible time off, paid holidays, and one week off between Christmas and New Year's.

• A platform for good: a culture of Diversity, Equity & Inclusion, charity matching and volunteer days-creating belonging for all is in our DNA both inside and outside of work.

• Remote-first culture. No matter where you are, you'll feel connected to the team.

• We take family seriously and offer flexible schedules and 12 weeks of paid parental leave.

• We give you great tools and tech to do your best work: Hardware, software, and home office setups.

 

The base salary range for this role is $160,000 to $200,000 annually based on full-time employment. Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc.

 

Our Interview and Hiring Process

We want the best people on our team. To get them, we've built our hiring process around three Ts: thorough, transparent and thoughtful. Our interview process is an honest evaluation of what you've done, what you're good at, and what you're working on improving. The goal of this process is to identify, as objectively as possible, people who will raise the level of play within our company.

Here's how it works:

• Application

• Screening interview - phone call (30 minutes)

• Deep dive interview with the hiring manager - video call (90+ minutes)

• Focused interviews with select potential teammates - 2 video calls (45 mins each)

• Reference calls with your last several managers

• Offer letter