Engineering Journal Jobs in Alameda Ca Remote

Open date: March 5, 2026

Next review date: Friday, Mar 20, 2026 at 11:59pm (Pacific Time)

Apply by this date to ensure full consideration by the committee.

Final date: Friday, Apr 10, 2026 at 11:59pm (Pacific Time)

Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.

The Chang Lab, led by PI Serina Chang, is part of the Berkeley EECS Department, the UCSF UC Berkeley Joint Program in Computational Precision Health, the Berkeley AI Research (BAIR) Lab, and the Center for Human-Compatible AI (CHAI).

We are seeking a postdoc to work on projects at the intersection of AI and human behavior, including modeling human behavior with AI, building AI tools to support societal decision-making, and studying the impacts of AI on society. Potential projects include:

1. 
   
2. Developing AI models of individuals that can accurately simulate complex behaviors across modalities, supported by rich, individual-level data including mobility trajectories, surveys, in-depth interviews, and health behaviors and outcomes.
   
3. Scaling simulations to entire societies with millions of agents, developing robust validation of societal simulations, and applying societal simulations to inform decisions in high-stakes domains (e.g., public health, emergency response).
   
4. Studying the impacts of generative AI on human health and well-being, from individual-level human-AI interactions (e.g., mental health risks, health decision-making) to community-level dynamics (e.g., changing support networks, engagement with health systems).
   

The selected candidate will assist with leading research projects, work closely with PI Serina Chang, mentor junior students in the lab, and help with the management of the lab.

Union: resources/employment-policies-contracts/bargaining-units/postdoctoral-scholars/contract/

PhD degree or equivalent international degree, or enrolled in a PhD or equivalent international degree granting program

PhD degree or equivalent international degree

• 
  
• PhD in Computer Science or closely related field
  
• Demonstrated record of publications in relevant computer science venues and/or general science journals
  
• Experience with training and evaluating generative AI models, working with large-scale messy datasets (e.g., mobility data, health data), and interdisciplinary research (e.g., computational social science, AI for health)
  
• 2-year postdoc is preferred, but we will consider applications for 1-year postdocs
  

• Curriculum Vitae - Your most recently updated C.V.

  
  

• Representative paper - Please include one research paper where you played a substantial role and that are representative of your work and interests.

  
  

• Second Representative paper - Please include one research paper where you played a substantial role and that is representative of your work and interests.

  
  

• Statement of Research - (max 4 pages). Please discuss your past research and accomplishments (e.g., publications, awards, presentations, evidence of real-world impact). Please also describe your plans for future research, especially how they would align with this position.

  
  

• Mentorship statement - (max 1 page). Please describe your past experience with mentoring junior students, including PhD students, master's, or undergraduate, and your philosophy towards mentorship. This could include mentoring students on research projects and/or teaching experience.

  
  

• 3 required (contact information only)

Help contact:

UC Berkeley is committed to diversity, equity, inclusion, and belonging in our public mission of research, teaching, and service, consistent with UC Regents Policy 4400 and University of California Academic Personnel policy (APM 210 1-d). These values are embedded in our Principles of Community, which reflect our passion for critical inquiry, debate, discovery and innovation, and our deep commitment to contributing to a better world. Every member of the UC Berkeley community has a role in sustaining a safe, caring and humane environment in which these values can thrive.

The University of California, Berkeley is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.

For more information, please refer to the University of California's Affirmative Action and Nondiscrimination in Employment Policy and the University of California's Anti-Discrimination Policy.

In searches when letters of reference are required all letters will be treated as confidential per University of California policy and California state law. Please refer potential referees, including when letters are provided via a third party (i.e., dossier service or career center), to the UC Berkeley statement of confidentiality prior to submitting their letter.

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

Unless stated otherwise, unambiguously, in the position description, this position does not include sponsorship of a new consular H-1B visa petition that would require payment of the $100,000 supplemental fee.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.

• 
  
• "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment or discrimination, as defined by the employer.
  
• UC Sexual Violence and Sexual Harassment Policy
  
• UC Anti-Discrimination Policy
  
• APM - 035: Affirmative Action and Nondiscrimination in Employment
  

Fractal is a strategic AI partner to Fortune 500 companies, with a bold vision: to power every human decision in the enterprise. We believe the future belongs to organizations that combine human imagination with intelligent systems—and Fractalites are the ones building that future. As we scale our Technology, Media & Telecom (TMT) practice in the United States, we are looking for a senior, client-facing Head of Engineering to shape and deliver world-class Data & AI platforms for leading Technology, Media & Telecom organizations.

This is not a back-office engineering role. This is a consulting-led, client-facing engineering leadership position for someone who is equally comfortable whiteboarding architecture with principal engineers, rolling up their sleeves with delivery teams, and advising CIOs, CTOs, and CDOs in the boardroom.

Learn more at Fractal | Intelligence for Imagination.

Note: This position is not eligible for Immigration Sponsorship at this time.

About the Role

This is a four-axis leadership role requiring technical depth, executive presence, team leadership, and embedded delivery. You'll work directly with top technical and functional leaders at some of the largest TMT companies in the world.

As Head of Engineering for Fractal's Technology, Media & Telecom (TMT) vertical, you will personally shape the architecture of mission-critical AIML platforms, often in first-party tech stack, and develop/drive the team of ICs who bring them to life.

Responsibilities

Some engagements will look like a traditional advisory model. Others will look a lot more like Forward Deployed Engineering: your team embedded inside a client's engineering org, working within their first-party tech stack, shipping production code alongside their engineers, and earning influence through technical credibility, not org chart position.

You will need to be in the room when the technology roadmap needs to change. When a business pivot, a new regulation, or a technology shift forces a rethink mid-execution, you are the person who picks up the marker, walks to the whiteboard, and redraws the architecture in real time, credibly, for the CTO, and Principal Engineering leaders simultaneously.

Technical Depth (Hands-On Architecture)

• Own AI/Data platform architecture decisions — from Lakehouse design and real-time streaming to MLOps, LLMOps, and AgentOps pipelines in production
• Serve as the technical authority for Fractal's TMT engineering practice — defining standards, reviewing design, and holding the bar on reliability, scalability, and security
• Translate ambiguous business problems into concrete, buildable platform architectures — and stay close enough to execution to know when something is not working
• Drive the industrialization of GenAI: moving clients from proof-of-concept to enterprise-grade, governed, and observable AI systems

Executive Presence & Live Architectural Thinking

• Command the room with senior client leadership — CIOs, CTOs, CDOs, and their direct reports - as a peer, not a vendor
• Whiteboard new architectural directions on the spot: when a business pivot, acquisition, regulatory shift, or technology breakthrough forces a mid-execution rethink, you synthesize it into a credible, buildable path forward live, in the room, without needing a week to prepare a deck
• Translate between two worlds simultaneously: make the architecture legible to a CFO and rigorous enough to satisfy a principal engineer in the same session
• Shape client roadmaps at the strategic level; identifying where the current plan is under-ambitious, over-engineered, or misaligned with emerging AI capabilities, and steering accordingly
• Represent Fractal at the highest level of client relationship

Team Leadership (Building & Driving Senior ICs)

• Develop and lead a high-performing group of individual contributors. principally senior and staff engineers, ML engineers, and data platform engineers
• Create the engineering culture: rigorous delivery standards, architectural thinking, and a bias toward elegant, production-grade solutions over quick fixes
• Build leadership depth within the team, identifying principals who can own programs and grow into broader roles
• Partner across Fractal's global AI and engineering Capability functions to staff programs strategically and raise capability across the TMT practice

Forward-Deployed & Embedded Delivery

• Lead and run FDE-style engagements where your team operates inside the client's engineering environment
• Navigate and deliver within client-owned, first-party technology stacks: proprietary data platforms, internal ML infrastructure, custom orchestration systems, and bespoke toolchains that do not appear in any industry survey
• Adapt quickly to non-standard environments, understanding a client's internal platform deeply enough to extend it, integrate into it, and earn the trust of their engineering staff
• Balance the tension between what Fractal does best and what the client's stack demands, knowing when to bring pattern, when to adapt, and when to advocate for a better path
• Set the standards for how Fractal operates in deeply embedded engagements: how we onboard, document, transfer knowledge, and leave clients stronger than we found them

Candidate Profile

Technical Qualifications

TMT clients bring genuinely hard problems on both open and proprietary infrastructure. Expect to architect and oversee:

• GenAI systems: RAG architectures, LLM fine-tuning pipelines, agentic workflow orchestration, and LLMOps observability
• AI-powered products: personalization engines, churn prediction, content recommendation, and network fault detection
• Client-proprietary ML infrastructure: internal feature stores, custom model serving layers, bespoke experiment tracking systems, and first-party orchestration frameworks
• Cloud-native infrastructure across AWS, Azure, and GCP with enterprise-grade governance, security, and compliance baked in
• Real-time and event driven data pipelines (e.g. network telemetry)
• Modern Lakehouse platforms (Databricks, Snowflake, Delta Lake, Iceberg) at petabyte scale and proprietary data platform equivalents at leading tech-forward TMT organizations

Non-technical Qualifications

We are particularly interested in leaders from environments where engineering rigor, client accountability, executive presence, and AI depth all coexist including Forward Deployed Engineering, elite data/ML platform teams, and senior hyperscaler architecture practices.

• 15–20 years of experience spanning AI/data engineering and technical leadership with clear evidence of owning architecture at scale
• Deep hands-on experience deploying AI/ML/GenAI systems in production, in addition to advising on them
• Demonstrated executive presence: you have walked into a CTO or CDO review, redrawn the architecture based on new constraints, and left the room with alignment
• The ability to whiteboard fluently under pressure, synthesizing a team's in-flight work with a new business direction, making it rigorous enough for engineers and clear enough for executives, on the spot and without a rehearsal
• Experience operating within client-owned or non-standard technology stacks - you have learned a proprietary system, earned trust from skeptical internal engineers, and delivered production-grade results inside someone else's infrastructure
• A track record of leading senior engineers and building high-performance ML/engineering teams, including hiring, coaching, and developing principal-level ICs
• Direct executive engagement experience - you have influenced CIO/CTO/CDO decisions and can hold your own in a room with technical and non-technical stakeholders at once
• Strong cloud-native fluency across one or more hyperscalers, with genuine depth in data platform patterns (streaming, batch, Lakehouse, governance)

Strong Preferences

• Experience in TMT vertical — hi-tech, telco, media platforms, streaming infrastructure, ad tech, or content delivery at scale
• Prior work in FDE-style or embedded delivery models where your team shipped inside a client codebase and was evaluated by their engineering standards, not just deliverable milestones
• Comfort with the ambiguity of 1P stack environments: you have debugged undocumented internal tools, extended proprietary frameworks, and figured out how to make external expertise land inside a closed ecosystem
• A personal reputation for architectural clarity: the person colleagues call when a problem needs to be drawn, not just describe
• Contributions to the ML/AI community: open source, publications, conference talks, or influential architectural patterns

Who Thrives Here

The Fractalite mindset is curious, rigorous, and impact driven. You will thrive in this role if you:

• Enjoy being client-facing and accountable for outcomes.
• Are comfortable navigating ambiguity, scale, and complex stakeholder environments.
• Believe great platforms come from strong engineering culture plus disciplined execution.
• See AI not as a novelty, but as a core enterprise capability that must be engineered responsibly.

Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Talent Acquisition Manager – AI Infrastructure & Engineering

San Francisco, California

Hybrid Working

We are expanding our global team and launching a new office in San Francisco.

WNTD is looking for an experienced Talent Acquisition Manager to join our Talent Solutions team and support the continued growth of AI infrastructure and accelerated compute platforms across North America.

This role will support one of the most significant AI infrastructure expansion programmes currently underway, focused on building next generation platforms powered by NVIDIA accelerated compute.

You will work closely with senior technical leaders to attract and hire talent across the full infrastructure stack including software engineering, AI platforms, GPU environments and large scale compute infrastructure.

This is a delivery focused role supporting high growth engineering programmes across AI infrastructure and cloud platforms.

The Role

You will lead hiring across multiple engineering disciplines spanning software engineering, AI infrastructure platforms and high performance compute environments.

Working closely with technical leadership and programme stakeholders, you will build pipelines of high quality candidates and manage fast moving hiring plans across several technical workstreams.

Key Responsibilities

• Build and manage talent pipelines across software engineering, AI infrastructure and GPU compute environments

• Proactively source talent across the United States through mapping, referrals and direct outreach

• Screen candidates for technical capability, experience and long term fit

• Partner with engineering leaders to define hiring priorities and role requirements

• Maintain clear tracking of hiring pipelines and delivery progress

• Support wider Talent Solutions activity during peak delivery phases

• Ensure a professional and consistent candidate experience

• Champion fair and inclusive hiring practices

Key Experience

• Proven experience hiring across complex engineering environments

• Strong track record building pipelines across software and infrastructure roles

• Comfortable engaging with technical stakeholders and discussing engineering topics

• Excellent communication and stakeholder management skills

• Strong organisation with the ability to manage multiple roles simultaneously

What We Offer

• Competitive salary and benefits

• Opportunity to support one of the fastest growing AI infrastructure build programmes globally

• Growth within a high performing delivery focused team

• Hybrid working model

• A collaborative culture that values ownership, pace and problem solving

Additional Requirements

• Ability to commute to the San Francisco office

• No visa sponsorship available

• Hybrid working model

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

Production Engineering at Pinterest is an evolution of our Site Reliability Engineering organization blending a hybrid of systems and software engineering with a focus on scaling, resiliency, reliability, performance, and efficiency. Our organization accomplishes this through building & integrating software, increasing automation, and infusing our knowledge & best practices into our Platform products so we can scale our large distributed systems to keep our customers happy, and our Pinners inspired. We also do this by developing short and long term embedded engagements with our engineering partners to help remove barriers, up-level reliability & best practices, and maintain a high consistent bar for reliability in a fast paced ever changing environment. We are always on a mission to improve reliability while also increasing engineering velocity, reducing toil and KTLO impact for both ourselves and our customers: fast, efficient, quality - we will accomplish all three!

What you'll do:

• 
  
• Lead our engineers to deliver on the biggest impact work across engineering to ensure we're infusing best practices into our products relating to reliability, scalability, performance and efficiency
  
• Drive technical architecture discussions; including being capable of driving and decision making for technology or applications that you have not had previous experience with
  
• Continuously assess your team's performance, address and coach under-performance, and recognize and promote high performance
  
• Create an inclusive and welcoming workplace where every team member feels valued and supported
  
• Foster an environment of open and honest communication, allowing team members to be safe to fail, encourage risk taking with a fail-fast mentality, and establish forums where they can share their ideas
  
• Empower engineers to develop their careers, matching their strengths with projects tailored to their skill levels, long-term skill development, personalities, and work styles
  
• Create an inspiring team charter and direction that align with the goals of the broader Production Engineering organization
  
• Develop strong partnerships with Product & Program Management partners across infrastructure by communicating a clear and impactful vision and priorities
  
• Establish team norms around planning, execution, and continuous improvement
  

What we're looking for:

• 
  
• 3+ years experience managing teams within an SRE, Production Engineering or other Platform/Infrastructure organizations
  
• Customer obsession: Demonstrated ability to work cohesively and build relationships with partners across engineering disciplines and capable of influencing without authority
  
• Familiarity with the concepts and use cases for SDLC including SCM tools, Build platforms, test frameworks, CI/CD products
  
• Familiar with usage and high level architecture of data platform technologies such as relational databases, storage & caching, key value stores, time series data stores, etc.
  
• Strong domain expertise in reliability concepts and best practices with the ability to innovate and provide thought leadership and direction in this problem space
  
• Hands on familiarity with public cloud platforms such as AWS, GCP, or Azure
  
• Knowledge of Linux systems internals and networking
  
• Thrive in an environment with a lot of ambiguity with the ability to be self sufficient and ruthlessly prioritize the highest impact projects
  
• Infrastructure technologies such as Docker, Kubernetes, Tensorflow, ElasticSearch, ZooKeeper, and Infrastructure as code (e.g. Terraform, Puppet, Chef, Ansible, Salt, Fabric, etc)
  
• Heavy bias toward action; able to drive resolution and making quick decisions balancing being data driven along with leveraging your experience & judgement
  

In-Office Requirement Statement:

• 
  
• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
  
• This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.
  

Relocation Statement:

• 
  
• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  

#LI-REMOTE

#LI-JT1

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

Our Commitment to Inclusion:

Open date: June 14, 2025

Most recent review date: Tuesday, Jul 29, 2025 at 11:59pm (Pacific Time)

Applications received after this date will be reviewed by the search committee if the position has not yet been filled.

Final date: Tuesday, Aug 25, 2026 at 11:59pm (Pacific Time)

Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.

The College of Chemistry at the University of California, Berkeley is generating an applicant pool of qualified lecturers to teach graduate courses on the Berkeley campus for the Master of Molecular Science and Software Engineering (MSSE) Program should an opening arise. We are seeking dynamic lecturers with a commitment to graduate education in computational science, data science, and software engineering to lead multiple courses each year. Disciplines where we are seeking instructors include:

• 
  
• Computational Chemistry
  
• Computational Quantum Chemistry
  
• Scientific Computing
  
• Machine Learning/Deep Learning
  
• Structural Bioinformatics
  
• High Performance Computing
  
• Complex mathematical modeling and simulations
  
• Leadership, management, and entrepreneurship
  

The MSSE Program is a unique program that is designed to formally train scientists, engineers, and computer scientists in computational and data science, and to provide them with the tools, software engineering practices, leadership, management, and entrepreneurial skills needed to create or lead science- or engineering-based enterprises. While the degree focuses on the molecular sciences, its content is suitable for any student pursuing software engineering or data science roles in other science-based industries, or in other areas that require advanced machine learning, complex mathematical modeling and simulations, or high-performance computing.

General Duties:

Classroom teaching and preparation, managing and mentoring graders and/or graduate student instructors (teaching assistants), holding office hours, assigning grades, advising students, preparing course materials (e.g., syllabus), and using Cal's electronic resources for course management.

The MSSE Program seeks candidates who can support the success of all students through inclusive curriculum, classroom environment, and pedagogy.

Program:

Contract for the Lecturers Unit (IX) between the University of California and the American Federation of Teachers:

Advanced degree or enrolled in an advanced degree program.

Advanced degree.

• 
  
• A Ph.D., or equivalent international degree, in an area related to computational science, data science, and/or software engineering
  
• Prior teaching and/or work experience in computational science, data science, and/or software engineering
  
• Leadership, management, and entrepreneurial skills in STEM fields
  
• Existing authorization to work in the U.S.
  
• Proficient in C++ and Python programming languages
  

• Curriculum Vitae - Your most recently updated C.V.

  
  

• Cover Letter (Optional)

  
  

• Statement of Teaching

  
  

• 3-5 required (contact information only)

Help contact:

UC Berkeley is committed to diversity, equity, inclusion, and belonging in our public mission of research, teaching, and service, consistent with UC Regents Policy 4400 and University of California Academic Personnel policy (APM 210 1-d). These values are embedded in our Principles of Community, which reflect our passion for critical inquiry, debate, discovery and innovation, and our deep commitment to contributing to a better world. Every member of the UC Berkeley community has a role in sustaining a safe, caring and humane environment in which these values can thrive.

The University of California, Berkeley is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.

For more information, please refer to the University of California's Affirmative Action and Nondiscrimination in Employment Policy and the University of California's Anti-Discrimination Policy.

In searches when letters of reference are required all letters will be treated as confidential per University of California policy and California state law. Please refer potential referees, including when letters are provided via a third party (i.e., dossier service or career center), to the UC Berkeley statement of confidentiality prior to submitting their letter.

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

Unless stated otherwise, unambiguously, in the position description, this position does not include sponsorship of a new consular H-1B visa petition that would require payment of the $100,000 supplemental fee.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.

• 
  
• "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment or discrimination, as defined by the employer.
  
• UC Sexual Violence and Sexual Harassment Policy
  
• UC Anti-Discrimination Policy
  
• APM - 035: Affirmative Action and Nondiscrimination in Employment
  

Sr. Data Engineer (Hybrid)

Chicago, IL

The American Medical Association (AMA) is the nation's largest professional Association of physicians and a non-profit organization. We are a unifying voice and powerful ally for America's physicians, the patients they care for, and the promise of a healthier nation. To be part of the AMA is to be part of our Mission to promote the art and science of medicine and the betterment of public health.

At AMA, our mission to improve the health of the nation starts with our people. We foster an inclusive, people-first culture where every employee is empowered to perform at their best. Together, we advance meaningful change in health care and the communities we serve.

We encourage and support professional development for our employees, and we are dedicated to social responsibility. We invite you to learn more about us and we look forward to getting to know you.

We have an opportunity at our corporate offices in Chicago for a Sr. Data Engineer (Hybrid) on our Information Technology team. This is a hybrid position reporting into our Chicago, IL office, requiring 3 days a week in the office.

As a Sr. Data Engineer, you will play a key role in implementing
and maintaining AMA's enterprise data platform to support analytics,
interoperability, and responsible AI adoption. This role partners closely with
platform engineering, data governance, data science, IT security, and business
stakeholders to deliver highquality, reliable, and secure data products. This
role contributes to AMA's modern lakehouse architecture, optimizing data
operations, and embedding governance and quality standards into engineering
workflows. This role serves as a
senior technical contributor within the team-providing mentorship to junior
engineers and implementing engineering best practices within the data platform function,
in alignment with architectural direction set by leadership.

RESPONSIBILITIES:

Data Engineering & AI Enablement

• Build and maintain scalable data pipelines and
  ETL/ELT workflows supporting analytics, operational reporting, and AI/ML use
  cases.
• Implement best practice patterns for ingestion,
  transformation, modeling, and orchestration within a modern lakehouse
  environment (e.g., Databricks, Delta Lake, Azure Data Lake).
• Develop highperformance
  data models and curated datasets with strong attention to quality, usability,
  and interoperability; create reusable engineering components and automation.
• Collaborate with the Architecture Team, the Data
  Platform Lead, and federated IT teams to optimize storage, compute, and
  architectural patterns for performance and costefficiency.
• Build model-ready data sets and feature
  pipelines to support AI/ ML use cases; serve as a technical coordination point
  supporting business units' AI-related infrastructure needs.
• Collaborate with data scientists and AI Working
  Group to operationalize models responsibly and maintain ongoing monitoring
  signals.

Governance, Quality & Compliance

• Embed data governance, metadata standards,
  lineage tracking, and quality controls directly into engineering workflows;
  ensure technical implementation and alignment within engineering workflows.
• Work with the Data Governance Lead and business
  stakeholders to operationalize stewardship, classification, validation,
  retention, and access standards.
• Implement privacybydesign and securitybydesign
  principles, ensuring compliance with internal policies and regulatory
  obligations.
• Maintain documentation for pipelines, datasets,
  and transformations to support transparency and audit requirements.

Platform Reliability, Observability & Optimization

• Monitor and troubleshoot pipeline failures,
  performance bottlenecks, data anomalies, and platformlevel issues.
• Implement observability tooling, alerts,
  logging, and dashboards to ensure endtoend reliability.
• Support cost governance by optimizing compute
  resources, refining job schedules, and advising on efficient architecture.
• Collaborate with the Data Platform Lead on
  scaling, configuration management, CI/CD pipelines, and environment management.
• Collaborate with business units to understand
  data needs, translate them into engineering requirements, and deliver
  fit-for-purpose data solutions; share and apply best practices and emerging
  technologies within assigned initiatives.
• Work with IT Security and Legal/ Compliance to
  ensure platform and datasets meet risk and regulatory standards.
  

Staff Management

• Lead, mentor, and provide management oversight
  for staff.
• Responsible for setting objectives, evaluating
  employee performance, and fostering a collaborative team environment.
• Responsible for developing staff knowledge and
  skills to support career development.

May include other responsibilities as assigned

REQUIREMENTS:

1. Bachelor's degree in Computer Science, Engineering, Information Systems, or related field preferred or equivalent work experience and HS diploma/equivalent education required.
2. 5+ years of experience in data engineering within cloud environments
3. Experience in people management preferred.
4. Demonstrated hands-on experience with modern data platforms (Databricks preferred).
5. Proficiency in Python, SQL, and data
   transformation frameworks.
6. Experience designing and operationalizing
   ETL/ELT pipelines, orchestration workflows (Airflow, Databricks Workflows), and
   CI/CD processes.
7. Solid understanding of data modeling,
   structured/unstructured data patterns, and schema design.
8. Experience implementing governance and quality
   controls: metadata, lineage, validation, stewardship workflows.
9. Working knowledge of cloud architecture, IAM,
   networking, and security best practices.
10. Demonstrated ability to collaborate across
    technical and business teams.
11. Exposure to AI/ML engineering concepts, feature
    stores, model monitoring, or MLOps patterns.
12. Experience with infrastructureascode
    (Terraform, CloudFormation) or DevOps tooling.

The American Medical Association is located at 330 N. Wabash Avenue, Chicago, IL 60611 and is convenient to all public transportation in Chicago.

This role is an exempt position, and the salary range for this position is $115,523.42-$150,972.44. This is the lowest to highest salary we believe we would pay for this role at the time of this posting. An employee's pay within the salary range will be determined by a variety of factors including but not limited to business consideration and geographical location, as well as candidate qualifications, such as skills, education, and experience. Employees are also eligible to participate in an incentive plan. To learn more about the American Medical Association's benefits offerings, please click here.

We are an equal opportunity employer, committed to diversity in our workforce. All qualified applicants will receive consideration for employment. As an EOE/AA employer, the American Medical Association will not discriminate in its employment practices due to an applicant's race, color, religion, sex, age, national origin, sexual orientation, gender identity and veteran or disability status.

THE AMA IS COMMITTED TO IMPROVING THE HEALTH OF THE NATION