Principal Engineer, Platform Engineering & AI Enablement
About The Position
Alkermes is building the next generation of cloud, data, and AI capabilities to accelerate innovation across the enterprise. We are seeking a Principal Engineer to define and build the foundational platforms, automation, and engineering practices that enable secure, scalable, and reliable delivery of modern applications, analytics, and artificial intelligence solutions. This individual will lead the engineering foundations that support enterprise AI initiatives, including large language models, generative AI applications, model lifecycle management, observability, governance, and secure deployment. The role partners with INDIGO, Security, Infrastructure, Data Analytics, and delivery teams to simplify processes, improve developer productivity, and enable cloud, data, and artificial intelligence solutions. The role reports to the Senior Director, Emerging Technology and Engineering and follows a hybrid schedule of three days per week in the Waltham office. Success in this role will accelerate solution delivery, improve platform reliability, reduce operational overhead, and enable the secure adoption of AI technologies across Alkermes.
Requirements
- Bachelor's degree in computer science, Engineering, Information Technology, or related field or equivalent in practical experience.
- 10+ years of experience across software engineering, platform engineering, cloud engineering, or DevOps.
- 5+ years designing and operating enterprise cloud platforms, preferably on AWS.
- Strong hands-on experience with automated build and release pipelines, infrastructure managed as code, cloud security, and monitoring.
- Experience leading complex technical initiatives and influencing teams without direct authority.
- Experience supporting artificial intelligence, data, or analytics platforms.
- Experience in a regulated industry; life sciences experience is preferred.
- Demonstrated ability to work effectively in an Agile environment, including iterative planning, cross-functional collaboration, and continuous delivery.
- Strong communication skills with technical and nontechnical audiences
Nice To Haves
- AWS, Terraform, Ansible, CloudFormation, Kubernetes, Docker, GitLab, or GitHub.
- Monitoring platforms such as Datadog, Splunk, New Relic, or Grafana.
- Python, PowerShell, Bash, or similar scripting languages.
- Snowflake, machine learning operations, or generative artificial intelligence environments.
- Internal developer platforms, workflow automation, and self-service engineering.
- Relevant AWS, Kubernetes, or infrastructure automation certifications.
Responsibilities
- Define and deliver the enterprise platform engineering roadmap.
- Build reusable services, self-service capabilities, and standard patterns that help teams deliver solutions faster.
- Build and evolve Internal Developer Platform capabilities, self service engineering services, and standardized developer workflows.
- Automate repetitive work across cloud, data, artificial intelligence, and application delivery.
- Create tools, templates, and workflows that improve architecture intake, risk assessment, and solution reviews.
- Advise the Architecture Review Board on technical feasibility, platform fit, and risk.
- Set practical standards for source control, automated build and release pipelines, testing, and infrastructure managed as code.
- Standardize deployment, configuration, and release processes across teams.
- Improve developer experience through reusable workflows, guardrails, and approved tools.
- Measure platform adoption, delivery speed, quality, and reduction of manual effort.
- Design and operate secure, scalable, cost-effective cloud platform services in AWS.
- Establish monitoring, logging, alerting, service objectives, and incident response practices.
- Lead reliability improvements, post-incident reviews, disaster recovery, patching, and vulnerability management.
- Embed security and compliance controls into platform designs and automated delivery.
- Recommend tools and platform improvements based on cost, performance, reliability, and business value.
- Build reusable platform capabilities and cloud patterns for artificial intelligence, machine learning, analytics, and generative AI workloads.
- Partner with data and science teams to move solutions from development into reliable production use.
- Automate model deployment, monitoring, and lifecycle management.
- Apply governance requirements for validation, security, bias, explainability, and regulatory compliance.
- Evaluate emerging technologies that improve engineering productivity or business outcomes.
- Serve as a trusted technical advisor to senior technology leadership on platform engineering, cloud strategy, and AI enablement.
- Work across Architecture, Engineering, Security, Infrastructure, PMO and business teams to deliver shared outcomes.
- Mentor engineers and promote practical, consistent engineering practices.
- Influence technical decisions through hands-on expertise, clear communication, and sound judgment.
- Challenge inefficient ways of working and build capabilities that reduce reliance on external resources.
Benefits
- annual performance pay bonus
- competitive benefits package
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Principal
