Job description

At NAVEX, we’re transforming the world—making it safer, more ethical, and ensuring every voice is heard. That’s real impact. Our high-performance culture is driven by our values. We move with speed, passion and purpose — as one team. We are bold in our ideas, accountable in our actions, and committed to doing the right things right. The Associate AI Engineer contributes to the development, testing, deployment, and operation of AI-enabled applications and services at NAVEX. Working under the guidance of experienced engineers, you will develop well-defined components of production AI systems, including data pipelines, application services, model integrations, retrieval workflows, automated evaluations, and monitoring capabilities. The ideal candidate brings foundational experience in software development, data engineering, statistics, or machine learning and demonstrates the ability and interest to develop deeper expertise in generative AI, retrieval-augmented generation, agentic workflows, and production AI engineering. You’ll thrive in this hybrid role surrounded by an engaged, collaborative team deeply committed to innovation, speed, and measurable outcomes. Join us and help shape what’s next! What you’ll get: Meaningful Purpose. Your work helps organizations operate with integrity and protect their people—at a scale few companies can match. High-Performance Environment. We move with urgency, set ambitious goals, and expect excellence. You’ll be trusted with real ownership and supported to do the best work of your career. Candid, Supportive Culture. We communicate openly, challenge ideas—not people—and value teammates who embrace bold thinking and continuous improvement. Growth That Matters. You can count on authentic feedback, strong accountability, and leaders invested in your success so you can achieve real growth. Rewards for Results. We provide clear, competitive compensation designed to recognize measurable outcomes and real impact. What you’ll do: Develop and test Python components for AI applications, including generative AI, retrieval and agent workflows Build APIs, services and integrations that connect AI capabilities with enterprise applications and data platforms Develop data pipelines to extract, clean, transform and validate data for AI and machine-learning applications Support predictive modelling, feature engineering and statistical analysis to evaluate data quality and model performance Build automated tests and evaluation datasets; analyze errors and measure accuracy, reliability, latency and cost Support cloud deployment, monitoring and troubleshooting using established source control, code review and CI/CD practices Apply privacy, security and responsible AI safeguards; validate outputs and escalate quality, bias, compliance or model-risk concerns Collaborate across Engineering, Data and Product; document your work, communicate findings and risks, and apply feedback to strengthen your skills What you’ll bring: Bachelor’s or master’s degree in Computer Science, Data Science, Statistics, Engineering, Applied Mathematics, or another related quantitative discipline, or equivalent practical experience Foundational professional, internship, academic, or project experience in software engineering, data engineering, machine learning, or statistical computing Experience programming in Python Experience working with SQL and relational data Understanding of data structures, data transformation, and data-quality concepts Foundational knowledge of statistical analysis and machine-learning methods Experience with common data or machine-learning libraries such as pandas, NumPy, scikit-learn, or comparable technologies Familiarity with APIs, automated testing, debugging, source control, and software-development practices Ability to analyze technical problems and communicate findings clearly Ability to collaborate effectively within cross-functional teams Demonstrated interest in developing and operating production AI systems Bonus experience: Building data pipelines, Python APIs or predictive models, including feature engineering and evaluation Working with LLMs, prompts, RAG, embeddings, semantic search or AI agents and tool calling Using cloud platforms, containers, CI/CD or tools for model tracking, versioning and monitoring Applying responsible AI, privacy and risk controls to complex, sensitive or regulated data Culture Agility. Comfort working in a fast-paced, candid environment that values innovation, healthy debate, and follow-through Fuel performance and outcomes. Leverage your job competencies and champion NAVEX’s core values Our side of the deal: We’ll be clear, we’ll move fast, and we’ll invest in your success. You deserve to be supported, challenged, and rewarded for the impact you make—and we commit to doing that every step of the way. The starting pay for this role is $85,000 per annum. Discover how you can grow, lead, and make an impact by visiting our career page to learn more. NAVEX is an equal opportunity employer committed to including individuals of all backgrounds, including those with disabilities and veteran status.

Requirements

Must-haves

At NAVEX, we’re transforming the world—making it safer, more ethical, and ensuring every voice is heard. That’s real impact.
Our high-performance culture is driven by our values. We move with speed, passion and purpose — as one team. We are bold in our ideas, accountable in our actions, and committed to doing the right things right.
The Associate AI Engineer contributes to the development, testing, deployment, and operation of AI-enabled applications and services at NAVEX.
You’ll thrive in this hybrid role surrounded by an engaged, collaborative team deeply committed to innovation, speed, and measurable outcomes. Join us and help shape what’s next!
Meaningful Purpose. Your work helps organizations operate with integrity and protect their people—at a scale few companies can match.
High-Performance Environment. We move with urgency, set ambitious goals, and expect excellence. You’ll be trusted with real ownership and supported to do the best work of your career.
Candid, Supportive Culture. We communicate openly, challenge ideas—not people—and value teammates who embrace bold thinking and continuous improvement.
Growth That Matters. You can count on authentic feedback, strong accountability, and leaders invested in your success so you can achieve real growth.
Rewards for Results. We provide clear, competitive compensation designed to recognize measurable outcomes and real impact.
Develop and test Python components for AI applications, including generative AI, retrieval and agent workflows
Build APIs, services and integrations that connect AI capabilities with enterprise applications and data platforms
Develop data pipelines to extract, clean, transform and validate data for AI and machine-learning applications
Support predictive modelling, feature engineering and statistical analysis to evaluate data quality and model performance
Build automated tests and evaluation datasets; analyze errors and measure accuracy, reliability, latency and cost
Support cloud deployment, monitoring and troubleshooting using established source control, code review and CI/CD practices
Apply privacy, security and responsible AI safeguards; validate outputs and escalate quality, bias, compliance or model-risk concerns
Collaborate across Engineering, Data and Product; document your work, communicate findings and risks, and apply feedback to strengthen your skills
Bachelor’s or master’s degree in Computer Science, Data Science, Statistics, Engineering, Applied Mathematics, or another related quantitative discipline, or equivalent practical experience
Foundational professional, internship, academic, or project experience in software engineering, data engineering, machine learning, or statistical computing
Experience programming in Python
Experience working with SQL and relational data
Understanding of data structures, data transformation, and data-quality concepts
Foundational knowledge of statistical analysis and machine-learning methods
Experience with common data or machine-learning libraries such as pandas, NumPy, scikit-learn, or comparable technologies

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningpythonci/cdsql

Platform: dayforce
Effort: medium