Senior Staff Machine Learning Engineer at Workiva defining enterprise - level AI architecture and solutions. Leading technical direction and influencing secure AI platform design across multiple teams.
About the role
- Principal Applied AI/ML Engineer designing and delivering high-impact AI systems for Autodesk's Forma Construction Cloud. Collaborating across teams to tackle complex technical challenges.
Responsibilities
- Lead the architecture, design, and evolution of production-grade applied AI systems, including LLM, ML, retrieval, agentic, and automation-based capabilities
- Own the most complex technical problems across the stack, from model behavior and system design through infrastructure, reliability, quality, and operational scale
- Set technical direction for how AI solutions are built, integrated, evaluated, secured, monitored, and improved over time
- Drive platform and systems decisions across AWS environments, including performance, resilience, observability, security, and cost optimization
- Shape the design and optimization of data systems, including relational and graph databases, data access patterns, schema strategy, and query performance
- Lead infrastructure thinking for distributed and cross-regional services where availability, latency, failover, or scale require stronger architectural rigor
- Establish stronger engineering quality practices, including validation frameworks, automated testing, release discipline, QA strategy, and incident response maturity
- Translate ambiguous business or product opportunities into technical strategy, execution plans, and measurable outcomes
- Partner across engineering, product, data science, analytics, and business stakeholders to align priorities and drive decisions without requiring formal authority
- Provide technical leadership across a team of roughly 20 people by mentoring engineers, reviewing designs, clarifying tradeoffs, and raising the bar for execution
- Create structure in ambiguous environments by defining milestones, surfacing risks, tracking dependencies, and ensuring follow-through across distributed teams
Requirements
- Deep experience building and scaling production software systems with meaningful AI/ML components
- Python mastery and fluent with latest AI/ML research and implementations/patterns
- Proven success leading architecture and delivery for complex, cross-functional technical initiatives
- Strong hands-on engineering ability in backend systems, APIs, services, data pipelines, and production operations
- Significant experience with AWS administration and optimization, including cloud architecture, observability, security, reliability, and cost/performance tradeoffs
- Strong understanding of database systems design and optimization, especially relational systems, with graph database experience strongly preferred
- Ability to work effectively as a technical generalist across adjacent areas including DevOps, infrastructure engineering, quality/QA, and delivery planning
- Excellent judgment in ambiguous situations, including the ability to simplify, prioritize, and make sound tradeoff decisions
- Outstanding written communication, including architecture docs, technical strategy memos, design reviews, decision records, and async execution updates
- Outstanding verbal communication, with the ability to influence both technical and non-technical stakeholders
- Demonstrated success collaborating across geographies, functions, and time zones.
Benefits
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
- Bonuses
- Stock grants
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