Note: The job is a remote job and is open to candidates in USA. USDM Life Sciences is a consulting company that helps heavily regulated biotech, medical device, and pharmaceutical organizations implement GxP technologies and drive digital transformation. The Principal Technical AI & Solutions Consultant bridges hands-on AI, data, and integration delivery with business development, leading technical sales cycles, solution architecture, executive customer engagements, and cross-functional delivery teams.
Responsibilities
- Drive business development by identifying, qualifying, and advancing new opportunities across the life sciences industry with a focus on AI implementation, data and integration architecture, and IT-enabled operations
- Own the end-to-end sales cycle for technical and AI engagements, from initial customer discovery and solution scoping through proposal development, SOW authoring, RFP response, and contract execution
- Cultivate and maintain executive-level customer relationships, conducting compelling C-suite and VP-level conversations that connect technical capabilities to strategic business and regulatory outcomes
- Advise customers on the current AI landscape, including foundation model providers (OpenAI, Anthropic, Google, AWS), AI platforms, and life sciences-specific AI tooling, and translate this knowledge into practical, risk-managed deployment strategies
- Develop and deliver technically rigorous yet business-accessible presentations, demonstrations, and proof-of-concept builds that accelerate customer decision-making
- Architect, implement, and deliver AI and machine learning solutions within life sciences environments, including large language model (LLM) deployment, retrieval-augmented generation (RAG) pipelines, AI agents, and machine learning model integration into validated systems
- Design, build, and manage data pipelines that aggregate, transform, and deliver structured and unstructured data across cloud, on-premises, and hybrid environments (e.g., Azure Data Factory, AWS Glue, Databricks, Snowflake, dbt)
- Lead system integration efforts connecting enterprise platforms, including Veeva Vault, Salesforce, SAP, Oracle, MES, LIMS, and ERP systems, using RESTful APIs, message queues, and integration middleware
- Configure and administer life sciences IT systems, supporting platform migrations, cloud infrastructure deployments, and validated system implementations in GxP-compliant environments
- Lead cross-functional delivery teams through the full project lifecycle, ensuring technical quality, on-time delivery, and measurable outcomes
- Define project scopes, technical architectures, and deliverables in alignment with customer expectations and USDM delivery standards
- Build and mentor teams of technical consultants, establishing best practices in AI implementation, data engineering, and system integration within life sciences contexts
- Contribute to USDM thought leadership by authoring technical content, presenting at industry forums, and developing reference architectures and point-of-view materials on AI and data topics
- Stay current on the evolving AI landscape, including model releases, agentic frameworks, AI governance standards, and FDA guidance on AI/ML in regulated environments
- Collaborate with quality, compliance, and validation practice teams to ensure AI and technical solutions meet GxP requirements and can be delivered with appropriate validation rigor
- Support internal capability development by mentoring colleagues, contributing to technical accelerators and proven methodologies, and participating in USDM practice-building initiatives
- Participate in strategic account planning, pipeline reviews, and capability presentations with practice leadership and sales teams
Skills
- • 10+ years of experience in technical consulting, solutions architecture, data engineering, or IT implementation, with a minimum of 3 years focused on AI or machine learning solution delivery
- • Proven track record of driving business development, managing technical sales cycles, and closing professional services or software engagements with life sciences customers
- • Demonstrated ability to lead executive-level technical conversations and translate complex architectural concepts into clear, outcome-oriented business narratives
- • Hands-on experience designing and deploying AI solutions, including LLM-based applications, RAG architectures, AI agents, and ML model operationalization (MLOps)
- • Proficiency in building and managing data pipelines using modern data engineering tools (e.g., Azure Data Factory, AWS Glue, Databricks, dbt, Airflow, or equivalent)
- • Strong experience with system integration patterns and technologies, including RESTful APIs, ETL/ELT frameworks, message-based architectures (Kafka, Service Bus), and enterprise integration platforms (MuleSoft, Azure Integration Services, or equivalent)
- • Familiarity with life sciences platforms including Veeva Vault, Salesforce, SAP, Oracle, and/or LIMS/MES systems and their integration landscape
- • Working knowledge of GxP requirements, computer system validation (CSV/CSA), and 21 CFR Part 11 as they apply to AI and IT systems in regulated environments
- • Proficiency in at least one programming or scripting language (Python, SQL, JavaScript, or equivalent) used in data engineering or AI implementation contexts
- • Exceptional written and verbal communication skills, including demonstrated ability to craft proposals, SOWs, and RFP responses
- • Strong analytical, architectural, and problem-solving skills, with a track record of designing and delivering technically sound solutions to complex operational challenges
- • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field required
- • Operate primarily in a remote home-office environment with prolonged periods of sitting or standing at a desk and working on a computer
- • Operate standard office productivity equipment, including a computer, phone, scanner, and printer
- • Frequently communicate with customers and internal stakeholders via telephone, video conference, email, or instant message. Must be able to exchange accurate information in these situations
- • Travel to customer sites for onsite work as needed
- • Master's degree or MBA preferred
- • Cloud platform certification (e.g., AWS Solutions Architect, Microsoft Azure Solutions Architect, Google Professional Data Engineer) preferred
- • AI or machine learning certification (e.g., AWS Certified Machine Learning, Google Professional ML Engineer, or equivalent) preferred
- • Project Management Professional (PMP) certification preferred
Benefits
- Full-time employees are eligible for health, vision, and dental insurance.
- Full-time employees are eligible for life insurance, short and long-term disability, hospital indemnity, accident, and critical care coverage.
- Both full and part-time employees, who are at least 21 years of age, are eligible to participate in USDM's 401k plan.
- Full and part-time employees may be eligible for paid time off.
- All employees are eligible for USDM's rewards and recognition program.
- Operate primarily in a remote home-office environment.
Company Overview
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