Senior Architect, Data and GenAI

We are looking for an enthusiastic Senior GenAI and LLM Architect to join Credera’s Data capability group. The ideal candidate will lead project‑based teams in a client‑facing role to analyze large data sets and derive insights through machine learning and artificial intelligence techniques.

You will act as the primary architect and technical lead on projects to scope and estimate work streams, design technical solutions to meet business requirements, and serve as a technical expert in client communications. A typical day involves participating in design sessions, provisioning environments, and coaching junior resources on projects.

• 8+ years of proven experience in the architecture, design, and implementation of large‑scale, enterprise‑grade AI/ML solutions, including hands‑on statistical modeling and/or analytical experience in industry or consulting settings.
• Master’s degree in statistics, mathematics, computer science or a related field (PhD preferred).
• Experience with a variety of ML and AI techniques (e.g., multivariate/logistic regression, cluster analysis, predictive modeling, neural networks, deep learning, pricing models, decision trees, ensemble methods).
• Proficiency in programming languages such as Python, Tensor Flow, PyTorch, or Hugging Face Transformers for model development and experimentation.
• Strong understanding of NLP fundamentals, including tokenization, word embeddings, language modeling, sequence labeling, and text generation.
• Experience with data processing using Lang Chain, data embedding with LLMs, vector databases, and prompt engineering.
• Advanced knowledge of relational and non‑relational databases (SQL, No
  
  SQL).
• Proficient in large‑scale distributed systems (Hadoop, Spark, etc.).
• Experience designing and presenting compelling insights using visualization tools (RShiny, R, Python, Tableau, Power BI, D3.js, etc.).
• Passion for leading teams and providing formal and informal mentorship.
• Experience wrangling, exploring, transforming, and analyzing datasets of varying size and complexity.
• Knowledgeable of tools and processes to monitor model performance and data quality, including model‑tuning experience.
• Strong communication and interpersonal skills, and the ability to engage customers at a business level in addition to a technical level.
• Stay current with AI/ML trends and research; be a thought leader in the AI area.
• Experience with implementing machine learning models in production environments through one or more cloud platforms:
  • Google Cloud Platform
  • Azure cloud services
  • AWS cloud services

• Thrive in a fast‑paced, dynamic, client‑facing role where delivering solid work products to exceed high expectations is a measure of success.
• Contribute in a team‑oriented environment.
• Prioritize multiple tasks consistently to meet deadlines.
• Creatively solve problems in an analytical environment.
• Adapt to new environments, people, technologies, and processes.
• Excel in leadership, communication, and interpersonal skills.
• Establish strong work relationships with clients and team members.
• Generate ideas and understand different points of view.

For individuals hired to work in Colorado, the compensation range is $160,000–$205,000 USD.

• Health, mental health, vision, dental, and life insurance.
• Prescriptions, fertility, and adoption benefits.
• Community service days, paid parental leave, PTO, and 14 paid holidays.
• Matching 401(k) plan.
• Healthcare & dependent flexible spending accounts.
• Disability benefits.

Most projects do not require extensive travel. Some projects may involve up to 80% travel for a period, but the annual average for team members is typically 10%–30%. Travel preferences are considered when assigning roles.

Applicants must be authorized to work in the U.S. without the need for employment‑based visa sponsorship now or in the future; no sponsorship is available for any visa category.

All qualified applicants will receive consideration for employment without regard to race, color, religion, gender identity, sexual orientation, national origin, age, genetic information, veteran status, or disability.