Principal AI Platform Engineer & Cloud Foundations

Socket.dev

Waltham (MA)

Hybrid

USD 180,000 - 210,000

Full time

4 days ago

Be an early applicant

Application generator

A complete application in a minute — tailored resume and cover letter, ready to send.

Get past ATS filters

Benefits offered by this job

Hybrid work model

Job summary

Alkermes seeks a Principal Engineer to define and build foundational platforms, automation, and engineering practices for secure, scalable delivery of AI-enabled solutions. You will lead enterprise platform initiatives spanning AWS, DevOps, and internal developer platforms.

The role collaborates with Security, Infrastructure, Data Analytics, and delivery teams to accelerate solution delivery, improve platform reliability, and enable secure AI adoption. Hybrid in Waltham, MA with 3 days onsite.

Qualifications

Bachelor's degree or equivalent in a related field.

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 AI, ML, analytics, and generative AI workloads.
Partner with data and science teams to move solutions from development into production.
Automate model deployment, monitoring, and lifecycle management.
Apply governance 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 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.