Senior Director, AI Solutions

Alamar BiosciencesFremont, CA
2d$280,000 - $300,000

About The Position

At Alamar, we are passionate about enabling our customers to make scientific discoveries that translate into clinical outcomes and benefit patients. Our team is growing quickly as we develop innovative approaches to measure critical protein biomarkers from liquid samples that can enable the earliest possible detection of disease. We believe the next frontier in biology is enabled by measuring proteins at higher sensitivity in highly multiplexed assays at the push of a button, which is something only Alamar can do. As we build our team, we seek collaborative, driven, intellectually curious people committed to solving complex challenges. Our culture rewards accountability and cross functional teamwork because we believe this enables the kind of breakthrough thinking that will accelerate our mission. We are seeking a highly strategic and execution-oriented Senior Director of AI Solutions to lead the design, delivery, and evolution of AI agents and intelligent features that transform how our customers, partners, and internal teams leverage Alamar's differentiated capabilities. This role sits at the intersection of product innovation, technical implementation, and measurable business impact. The ideal candidate combines deep technical expertise with strong product instincts, exceptional project management capabilities, and the ability to move seamlessly between strategic planning and hands-on development. This is a senior individual contributor role reporting to the VP of AI & Strategic Initiatives. You will be responsible for defining strategic approaches to AI-powered solutions, driving end-to-end delivery of high-impact agents, and maintaining a portfolio of production systems that deliver measurable ROI. You must be equally comfortable architecting multi-agent systems, writing production code, managing complex cross-functional programs, and evangelizing adoption across diverse stakeholder groups.

Requirements

  • 12+ years of experience in technical roles spanning product development, AI/ML engineering, and solution delivery
  • Proven track record architecting and delivering production AI systems, intelligent agents, or ML-powered products that drove measurable business outcomes
  • Strong hands-on technical skills with modern agentic frameworks, Python programming, and API integration
  • Experience with RAG and GraphRAG systems, agent orchestration, tool-calling architectures, and LLM application development
  • Demonstrated ability to manage complex, multi-stakeholder technical programs from concept through production
  • Strong product instincts and user empathy - ability to translate user needs into technical requirements
  • Excellent communication skills with ability to engage effectively with technical and non-technical audiences
  • Self-directed and comfortable operating with ambiguity in fast-paced startup environments
  • Proven ability to drive adoption of new technologies through effective training, documentation, and change management

Nice To Haves

  • Experience in biotech, life sciences, or scientific software domains
  • Background in computational biology, bioinformatics, or omics data analysis
  • Familiarity with scientific data platforms, ELNs, LIMS systems, or laboratory informatics
  • Experience building customer-facing AI features or B2B SaaS products
  • Knowledge of data governance, regulatory requirements, or compliance frameworks (HIPAA, FDA, ISO)
  • Contributions to open-source AI/ML projects or active participation in AI development communities
  • Experience working with product management, go-to-market teams, or in customer-facing technical roles

Responsibilities

  • Define and drive strategic initiatives to increase accessibility and value delivery of Alamar's capabilities through intelligent features and AI-powered experiences
  • Identify opportunities where AI agents can accelerate operational excellence, reduce friction, and create measurable business outcomes
  • Co-develop roadmaps for AI solution development aligned with commercial, R&D, and customer success priorities
  • Partner with leadership to translate business objectives into technical requirements and executable project plans
  • Conduct user research, gather feedback, and iterate on solutions to drive adoption and demonstrate clear ROI
  • Stay current on emerging AI capabilities, tools, and competitive landscape to inform AI & Data strategy
  • Architect, build, and deploy production AI agents spanning commercial workflows, operational processes, and customer-facing features
  • Design multi-agent systems with appropriate orchestration, tool-calling, memory management, and state handling
  • Implement agents using modern frameworks and integrate with existing systems through APIs, MCPs, and custom connectors as needed
  • Write high-quality production code (Python, TypeScript, etc.) for agent logic, integrations, and supporting infrastructure
  • Build evaluation frameworks and observability systems to measure agent performance, reliability, and business impact
  • Establish versioning, deployment, and rollback strategies for production agent systems
  • Own the full lifecycle of delivered agents including ongoing maintenance, enhancement, and iteration based on usage patterns and feedback
  • Drive end-to-end project delivery from concept through production release, ensuring on-time delivery with high quality
  • Manage dependencies across the AI team, engineering, product, commercial, R&D, and operations teams
  • Create clear project plans with milestones, success metrics, and risk mitigation strategies
  • Facilitate stakeholder alignment through effective communication, demos, and progress reporting
  • Navigate technical and organizational complexity to unblock execution bottlenecks
  • Build adoption strategies including training materials, documentation, and change management support
  • Collaborate with data and AI platform team members to leverage foundational capabilities (data lakehouse, model serving, governance frameworks)
  • Build integration layers connecting agents to internal systems, external data sources, and third-party services
  • Implement governance frameworks, security, privacy, and compliance requirements appropriate for production AI systems
  • Optimize agent performance, cost, and scalability as usage grows
  • Contribute to shared tooling, libraries, and best practices that accelerate future agent development
  • Investigate and prototype AI/ML approaches to accelerate biological insight generation from Alamar data
  • Explore opportunities to streamline algorithm development workflows through intelligent automation
  • Identify and evaluate external datasets (public repositories, commercial subscriptions, partnerships) that could enhance AI solution capabilities
  • Build proof-of-concept integrations demonstrating value of new data sources or analytical approaches

Benefits

  • bonus
  • equity
  • benefits
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