Sr. Principal Software and AI Engineer

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Sr. Principal Software and AI Engineer based in the United States. Join a forward-thinking team developing advanced AI-powered applications that transform drug development and clinical trial execution. In this senior technical leadership role, you will shape AI engineering strategy while remaining hands-on in designing, building, and deploying production-grade software.

You will lead the development of intelligent, multi-agent systems that streamline clinical protocol generation and improve research workflows. Working closely with clinical experts, medical writers, statisticians, and data scientists, you will translate complex scientific challenges into scalable AI solutions. You will establish engineering standards for reliability, evaluation, security, and regulatory compliance within a validated software development lifecycle.

This is an opportunity to influence enterprise AI architecture, mentor engineering talent, and accelerate innovation in a highly regulated, mission-driven environment.

Accountabilities Lead AI application development

Architect, develop, and deploy production-ready AI-powered and agentic applications that support clinical protocol generation, study design, and clinical trial operations.

Define technical strategy and architecture

Establish scalable and reliable architectures for multi-agent orchestration, model integration, tool connectivity, and the complete LLMOps lifecycle.

Drive end-to-end product delivery

Take ownership of technical direction, project execution, priorities, scope, timelines, and software quality from initial concept through production deployment.

Establish AI engineering standards

Define and implement best practices for AI-native development, testing, evaluation, observability, continuous monitoring, and CI/CD within a rigorous software development lifecycle.

Advance AI capabilities

Evaluate emerging foundation models, open-weight models, agent frameworks, and development tools to make informed decisions about technology selection, model sourcing, and build-versus-buy strategies.

Develop enterprise knowledge systems

Design and maintain knowledge architectures, including ontologies, knowledge graphs, and retrieval systems that make complex scientific information structured, governed, and accessible to AI applications.

Ensure AI reliability and compliance

Implement evaluation frameworks combining expert benchmarks, rule-based validation, human review, and model-based assessments. Integrate data privacy, security, auditability, traceability, responsible AI practices, and human oversight into production systems.

Collaborate across disciplines

Partner with clinical, medical writing, biostatistics, data science, product, and clinical operations teams to identify opportunities and integrate AI into regulated clinical development workflows.

Mentor and develop engineering talent

Guide engineers through architecture discussions, code reviews, reference implementations, technical coaching, and hands-on collaboration while promoting engineering excellence.

Improve operational performance

Apply AI-assisted development tools and modern software engineering practices to increase developer productivity without compromising testing rigor, maintainability, or production quality.

Requirements Education

Bachelor's degree with at least 7 years of relevant experience, a master's degree with at least 5 years of experience, or a Ph.D. with at least 3 years of experience.

Professional experience

Extensive software engineering and AI/ML engineering experience, including principal-level or technical leadership responsibilities and ownership of large-scale AI products from concept through deployment.

Production AI expertise

A demonstrated track record of delivering reliable, production-grade AI and agentic applications with measurable scientific or business impact. Experience in pharmaceutical, biotechnology, life sciences, or other regulated industries is strongly preferred.

Full-stack software engineering

Strong backend development expertise in Python and/or .NET, with experience building enterprise applications across frontend interfaces, APIs, databases, and deployment environments.

Data architecture

Hands-on experience with relational, search, and graph databases, such as PostgreSQL, Elasticsearch, and Neo4j, alongside strong capabilities in system design, data modeling, and production operations.

Agentic AI and LLMs

Deep practical knowledge of multi-agent application development, agent harness design, context engineering, orchestration, tool integration—including Model Context Protocol (MCP)—and human-in-the-loop controls.

Model integration and optimization

Ability to select and apply frontier and open-weight models, implement structured outputs and guardrails, and validate model behavior. Experience with fine-tuning or post-training techniques is an advantage.

Knowledge engineering

Experience designing enterprise knowledge architectures, ontologies, knowledge graphs, and retrieval systems that support reliable AI-driven reasoning and information access.

AI evaluation and observability

Proven ability to develop layered evaluation strategies using expert benchmarks, rule-based checks, human assessments, model-based grading, and production monitoring.

Cloud and development infrastructure

Strong understanding of LLMOps, secure cloud deployment across AWS, Microsoft Azure, or Google Cloud Platform, and modern observability practices.

AI-assisted software development

Familiarity with AI coding tools and workflows, combined with disciplined testing, code review, continuous integration, and continuous delivery practices.

Clinical and regulatory knowledge

Experience in clinical protocol development, study design, or clinical trial operations is desirable. Familiarity with ICH M11 structured protocols, CDISC standards, USDM, GxP requirements, computer system validation, and emerging AI regulations in drug development is a strong advantage.

Leadership and communication

Proven ability to lead technical workstreams, mentor senior engineers, influence architectural decisions, and communicate complex technical concepts clearly to scientific, regulatory, business, and executive stakeholders.

Professional competencies

Strong analytical thinking, problem-solving, initiative, adaptability, collaboration, and commitment to data privacy, information security, responsible AI, and continuous improvement.

Travel

Willingness to travel approximately 10% of the time.

Benefits Competitive compensation

Annual base salary ranging from $137,400 to $182,400 , depending on qualifications, experience, skills, and work location.

Annual incentive opportunities

Eligibility for an annual bonus plan for non-commercial roles.

Equity participation

Opportunity to receive discretionary equity awards and participate voluntarily in an employee stock purchase plan.

Comprehensive healthcare

Medical, dental, and vision insurance options.

Retirement savings

401(k) plan to support long-term financial planning.

Flexible spending options

Access to flexible spending accounts (FSAs) and health savings accounts (HSAs), subject to eligibility.

Insurance protection

Life insurance and other applicable employee protection benefits.

Paid time off

Paid leave to support personal needs, rest, and work-life balance.

Wellness support

Access to wellness benefits and programs.

Remote work

Remote position based in the United States, offering flexibility in how work is organized.

Professional impact and growth

Opportunity to shape advanced AI engineering practices, mentor talented professionals, and contribute to technologies that can improve drug development and patient outcomes.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?

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