data engineer

software engineer

data scientist

advisor - scientific data engineer Jobs in San Francisco

advisor - scientific data engineer

ai data engineer (agent platform) Jobs in San Francisco

ai data engineer (agent platform)

data infrastructure engineer

Ｃollective

<div>About Collective:
Collective is on a mission to redefine the way businesses-of-one work. Our technology and team of trusted advisors help members achieve financial independence by taking care of everything from business incorporation to accounting, bookkeeping, tax services, and access to a thriving community, all in one integrated platform. We believe in empowering self-employed people to enjoy the same tax savings that big companies get, so they can focus on their passion, not paperwork.
Featured in Forbes, Business Insider, Yahoo, Bloomberg, Financial Times, TechCrunch, and more. We are backed by General Catalyst, Sound Ventures (Ashton Kutcher and Guy Oseary), QED Investors, Google&rsquo;s Gradient Ventures, Expa, and other investors who have financed iconic companies like YouTube, Substack, Twitch, Box, Hims, Instacart, and Lyft.
About the role:
Most teams have the data they need but can&rsquo;t access it. This role is here to fix that.
We're hiring a senior engineer to build an internal data agent: a system that lets anyone at the company act as their own data analyst. Individuals can ask questions in plain English and get back correct, decision-ready answers or dashboards.
This is not a traditional data role. You'll operate across AI systems, data infrastructure, and product engineering. You'll be responsible both for building a powerful system and for ensuring the data it relies on is clean, consistent, and reliable.
The problem space is wide open. We&rsquo;re looking for a strategic operator to shape the technical direction, the data model, and system adoption.
What you'll do:<ul><li>
Develop agent infrastructure<ul><li>
Build retrieval, planning, and execution systems on top of real data</li><li>
Support multi-step reasoning and analysis workflows</li><li>
Integrate into internal tools</li></ul></li><li>
 Build an end-to-end analytics system<ul><li>
Create a natural language interface over our entire data stack</li><li>
Enable anyone to run complex analyses without writing SQL</li></ul></li><li>
Own and improve the data layer<ul><li>
Collaborate with product engineering to design and evolve clean, consistent data models</li><li>
Identify inconsistencies in the core schema and resolve them at the source</li></ul></li><li>
Build and maintain data pipelines<ul><li>
Own the reliability of our data infrastructure end-to-end</li><li>
Debug and fix broken systems (e.g. dbt models, pipeline failures)</li><li>
Make it easy to integrate new data sources into the data warehouse</li></ul></li><li>
Make it trustworthy<ul><li>
Ensure outputs are correct, consistent, and explainable</li><li>
Build evaluation loops, monitoring, and guardrails</li><li>
Eliminate ambiguity in metrics, definitions, and sources of truth</li><li>
Handle permissions, sensitive data, and edge cases</li></ul></li><li>
Drive adoption<ul><li>
Work directly with teams across EPD, Member Operations, Legal, and more</li><li>
Drive alignment on data definitions and system usage</li><li>
Turn this into the default way people interact with data</li></ul></li></ul>
What you'll bring:<ul><li>
 You are a product engineer working in data<ul><li>
You treat data models as part of the product, not a separate layer</li><li>
You have strong opinions on schema design, naming, and consistency</li><li>
You're comfortable identifying issues in production data and fixing them at the root</li></ul></li><li>
You are an owner, not a participant<ul><li>
You take vague, high-stakes problems and turn them into real systems</li><li>
You care about outcomes, not just implementation</li></ul></li><li>
You have strong data experience<ul><li>
Experience with data modeling, warehouses, and pipelines</li></ul></li><li>
You're an exceptional builder<ul><li>
You can go from idea architecture production</li><li>
You've built with LLMs, RAG, or agents in production</li><li>
You've shipped systems that people actually rely on</li></ul></li><li>
You have influence<ul><li>
You communicate effectively with both technical and non-technical stakeholders</li><li>
You can drive alignment across teams with competing priorities</li><li>
You're comfortable challenging existing systems and pushing for better approaches</li></ul></li></ul>
What we offer:<ul><li>
Hybrid Work Model: Based in San Francisco with a balance of in-office and remote flexibility.</li><li>
Fresh Lunch: Provided on in-office days.</li><li>
Commuter Support: $150 monthly reimbursement for transit expenses.</li><li>
Health &amp; Wellness: $200 quarterly reimbursement to support your well-being.</li><li>
Time Off: Flexible PTO plus 14 company holidays.</li><li>
Comprehensive Coverage: 100% medical, dental, and vision for employees; 75% coverage for dependents.</li><li>
Parental Leave: 16 weeks fully paid.</li><li>
Retirement &amp; Ownership: 401k plan plus an equity package.</li><li>
Team Connection: Quarterly virtual events and an annual in-person summit.</li></ul>
Compensation Range: $200K - $270K</div>

AI Data Engineer (Agent Platform)

Cohere

<div>
 
 Who are we?
 
 
 
 Our mission is to scale intelligence to serve humanity. We&rsquo;re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.
 
 
 We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what&rsquo;s best for our customers.
 
 
 Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.
 
 
 Join us on our mission and shape the future!
 
 
 
 Why this role?
 
 
 
 We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most curious people to help us do it. As a member of our Analytics &amp; Data Insights team, you'll tackle the kind of problems that don't have textbook answers yet, launch products that didn't exist a year ago, and help enterprises understand what foundational AI actually means for their bottom line.
 
 
 
 As a Data Engineer, You Will
 
 
 
 <ul>
 <li>
 Work directly on storage infrastructure, product launches, and new customer experiences built on one of the most advanced AI systems in the world
 </li>
 <li>
 Collaborate daily with researchers and engineers who are some of the best in the world at what they do
 </li>
 <li>
 Run implementations end-to-end and see initiatives through to real outcomes &mdash; no waiting around to be told what to do
 </li>
 <li>
 Partner across research, marketing, sales, and finance to help define how Cohere grows, with your recommendations feeding directly into products and strategy
 
 
 </li>
 </ul>
 
 You May Be a Good Fit If You Have
 
 
 
 <ul>
 <li>
 5+ years of experience working on production-grade data processing systems
 </li>
 <li>
 Strong command of Python and SQL
 </li>
 <li>
 Experience with distributed data processing frameworks such as Apache Beam, Spark, or Flink
 </li>
 <li>
 The ability to transform unstructured data into performant datasets across diverse storage backends including S3, GCS, and POSIX
 </li>
 <li>
 Experience with modern orchestration platforms, especially Kubernetes (nice to have)
 </li>
 <li>
 Familiarity with modern analytics stack tooling such as BigQuery, Airflow, or dbt (nice to have)
 </li>
 <li>
 Knowledge of Java or Golang (nice to have)
 </li>
 <li>
 Genuine excitement about AI - you follow the research, have opinions, and enjoy being in the weeds
 </li>
 <li>
 Comfort operating at the edge of what's known, with a desire to build something genuinely new rather than optimise what already exists
 
 
 </li>
 </ul>
 If some of the above doesn&rsquo;t line up perfectly with your experience, we still encourage you to apply!
 
 
 We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.
 
 
 
 Full-Time Employees At Cohere Enjoy These Perks
 
 
 
 🤝 An open and inclusive culture and work environment
 
 
 🧑&zwj;💻 Work closely with a team on the cutting edge of AI research
 
 
 🍽 Weekly lunch stipend, in-office lunches &amp; snacks
 
 
 🦷 Full health and dental benefits, including a separate budget to take care of your mental health
 
 
 🐣 100% Parental Leave top-up for up to 6 months
 
 
 🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
 
 
 🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
 
 
 ✈️ 6 weeks of vacation (30 working days!)
</div>

Data Engineer

Figma

<div>
 Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma&rsquo;s platform helps teams bring ideas to life&mdash;whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us!
 
 
 We are looking for an experienced Data Engineer to partner with our Data Science and Data Infrastructure teams to own and scale our data pipelines. You&rsquo;ll also work closely with stakeholders across business teams including sales, marketing, and finance to ensure that the data they need arrives promptly and reliably. You&rsquo;ll play an integral role in building the metrics and self-serve reporting capabilities to unlock Figma&rsquo;s next phase of growth.
 
 
 This is a great role for an individual who is passionate about working with data and data systems, and who loves solving problems. You&rsquo;ll have a good sense for when it makes sense to build fast, scrappy solutions to unblock a key stakeholder vs. when to push back or bring in an outside service. The ideal candidate will be a great communicator who can help coordinate across multiple internal and external teams and takes pride in building end-to-end projects.
 
 
 This is a full time role that can be held from one of our US hubs or remotely in the United States.
 
 
 
 What you'll do at Figma
 
 
 :
 
 
 
 <ul>
 <li>
 Own, build, and maintain scalable data pipelines that connect various cloud data sources.
 </li>
 <li>
 Develop a deep understanding of Figma&rsquo;s core data models and optimize data pipelines for scale.
 </li>
 <li>
 Partner with the Data Science and Data Infrastructure teams to build new foundational data sets that are trusted, well understood, and enable self-service.
 </li>
 <li>
 Work with a wide range of cross-functional stakeholders to derive requirements and architect shared datasets; ability to document, simplify and explain complex problems to different types of audiences.
 </li>
 <li>
 Establish best practices for the development of specialized data sets for analytics and modeling.
 
 
 </li>
 </ul>
 We'd love to hear from you if you have:
 
 
 <ul>
 <li>
 4+ years in a relevant field.
 </li>
 <li>
 Fluency with both SQL and Python.
 </li>
 <li>
 Familiarity with Snowflake, dbt, Dagster, and ETL/reverse ETL tools.
 </li>
 <li>
 Excellent judgment and creative problem solving skills.
 </li>
 <li>
 A self-starting mindset along with strong communication and collaboration skills.
 
 
 </li>
 </ul>
 While not required, it&rsquo;s an added plus if you also have:
 
 
 <ul>
 <li>
 Knowledge in data modeling methodologies to design and build robust data architectures for insightful analytics.
 </li>
 <li>
 Experience with business systems such as Salesforce, Customer IO, Stripe, NetSuite is a big plus.
 
 
 </li>
 </ul>
 At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you&rsquo;re excited about this role but your past experience doesn&rsquo;t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
 
 
 
 Pay Transparency Disclosure
 
 
 
 If based in Figma&rsquo;s San Francisco or New York hub offices, this role has the annual base salary range stated below.
 
 
 Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. The listed range is a guideline, and the range for this role may be modified. For roles that are available to be filled remotely, the pay range is localized according to employee work location by a factor of between 80% and 100% of range. Please discuss your specific work location with your recruiter for more information.
 
 
 Figma offers equity to employees, as well a competitive package of additional benefits, including health, dental &amp; vision, retirement with company contribution, parental leave &amp; reproductive or family planning support, mental health &amp; wellness benefits, generous PTO, company recharge days, a learning &amp; development stipend, a work from home stipend, and cell phone reimbursement. Figma also offers sales incentive pay for most sales roles and an annual bonus plan for eligible non-sales roles. Figma&rsquo;s compensation and benefits are subject to change and may be modified in the future.
 
 
 Annual Base Salary Range:
 
 
 $140,000&mdash;$348,000 USD
 
 
 At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status
 
 ,
 
 or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
 
 
 We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com. These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities.
 
 
 Examples of accommodations include but are not limited to:
 
 
 <ul>
 <li>
 Holding interviews in an accessible location
 </li>
 <li>
 Enabling closed captioning on video conferencing
 </li>
 <li>
 Ensuring all written communication be compatible with screen readers
 </li>
 <li>
 Changing the mode or format of interviews
 
 
 </li>
 </ul>
 To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding.
 
 
 By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice.
</div>

Eli Lilly

<div>At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We&rsquo;re looking for people who are determined to make life better for people around the world.<h1 class="jobSectionHeader">
The Opportunity</h1>
We are building something unprecedented &mdash; an AI foundation that will push the frontier on what is possible today across drug discovery research, from target identification and disease biology through translational science.
The Applied Intelligence for Discovery (AI4D) team is a newly formed group within Lilly Research Laboratories that operates at the intersection of scientific delivery and core platform development. AI4D&rsquo;s mission is connecting scientists to petabyte-scale data through natural language interfaces, automated analysis workflows, and intelligent search &mdash; and to convert early deployments into repeatable system standards and evaluation practices that scale across therapeutic areas.
As a Scientific Data Engineer, you will close that gap. You will build the semantic layer, data harmonization infrastructure, AI-ready data products, and lakehouse architecture that bridge how data is stored and how AI systems need to consume it. You will be working at the intersection of the data infrastructure team and the generative AI engineers who build the systems scientists interact with.<h1 class="jobSectionHeader">
Responsibilities</h1><h2 class="jobSectionHeader">
Data Harmonization and Lakehouse Architecture</h2><ul><li>
Design and build the data architecture that transforms raw and processed omics data into harmonized, AI-consumable layers</li><li>
Build and optimize ETL/ELT pipelines that produce denormalized views, pre-computed aggregations, embedding-ready text representations, and feature stores optimized for AI system consumption</li><li>
Implement data quality monitoring, automated profiling, and validation checks across harmonization layers</li><li>
Create versioned, reproducible data snapshots that support model training, evaluation, and audit requirements in a regulated environment</li><li>
Partner with the teams to extend harmonization patterns as data modalities expand beyond genomics and proteomics into spatial transcriptomics, perturbational data (Perturb-Seq), single-cell, and digital pathology</li></ul><h2 class="jobSectionHeader">
Semantic Layer and Schema Engineering</h2><ul><li>
Design and maintain a semantic layer over Lilly&rsquo;s multi-omics databases that enables AI systems</li><li>
Create comprehensive schema documentation: table descriptions, column-level annotations, relationship mappings, business logic rules, and domain-specific constraints (e.g., statistical thresholds, unit conventions, experimental design metadata)</li><li>
Develop gold-standard question/SQL pairs for each major database, in collaboration with computational biologists and Generative AI Engineers, to serve as training data, few-shot examples, and evaluation benchmarks</li><li>
Build and maintain a data dictionary and ontology mapping layer that translates how scientists think and speak about data (gene names, pathway terms, assay types) into how the data is physically stored</li></ul><h2 class="jobSectionHeader">
AI-Ready Data Products</h2><ul><li>
Build and manage vector embedding pipelines for scientific documents, study metadata, and structured data descriptions to power RAG-based retrieval</li><li>
Build integration pipelines that connect heterogeneous data sources &mdash; omics databases, internal publications, electronic lab notebooks, assay results, and clinical annotations &mdash; into a unified, queryable layer</li><li>
Develop and enforce metadata standards that ensure new data sources are AI-accessible from the point of ingestion, not retroactively</li><li>
Design data products that serve multiple consumption patterns: direct SQL access for computational biologists, structured feeds for ML training pipelines, and semantic interfaces for LLM-powered tools</li></ul><h1 class="jobSectionHeader">
Qualifications</h1><ul><li>
Bachelors degree in Computer Science, Data Engineering, Bioinformatics, or a related field + 8 years data engineering experience OR Masters degree and 5 years data engineering experience</li><li>
Demonstrated expertise in building data pipelines, ETL/ELT workflows, and data products that serve downstream AI/ML systems</li></ul><h1 class="jobSectionHeader">
Additional Skills/Preferences</h1><ul><li>
Phd in data or related field</li><li>
Strong SQL skills and experience with complex relational database schemas (hundreds of tables, multi-level joins, domain-specific conventions)</li><li>
Experience with modern data platform technologies, including at least one of: Databricks, Snowflake, or equivalent lakehouse platforms</li><li>
Experience with modern data engineering tools: dbt, Spark, Airflow, or similar orchestration and transformation frameworks</li><li>
Proficiency in Python for data processing, scripting, and pipeline development</li><li>
Experience with cloud data platforms (AWS preferred: Redshift, Athena, Glue, S3, or similar)</li><li>
Familiarity with at least one of: vector databases, embedding pipelines, or semantic layer tooling</li><li>
Strong communication skills &mdash; you can work effectively with both engineers who think in schemas and scientists who think in biology</li><li>
Experience with biomedical or scientific data: omics datasets (RNA-seq, proteomics, GWAS), clinical data, or laboratory information management systems</li><li>
Experience in pharmaceutical, biotech, or life sciences environments</li></ul><ul><li>
Familiarity with biomedical ontologies and controlled vocabularies (Gene Ontology, MeSH, ChEBI, HGNC) and their application to data integration</li><li>
Experience building data products that serve AI/ML systems &mdash; feature stores, training datasets, evaluation benchmarks, or semantic annotations for text-to-SQL</li><li>
Knowledge of data governance practices in regulated industries: data lineage, access controls, versioning, and auditability</li><li>
Experience with knowledge graph technologies (Neo4j, Amazon Neptune, RDF/SPARQL) or graph-based data modeling</li><li>
Deep experience with Databricks ecosystem: Unity Catalog for data governance, Delta Lake for ACID transactions, MLflow integration, and Databricks SQL for analytics workloads</li><li>
Experience designing data architectures that bridge traditional bioinformatics workflows (Nextflow, R/Bioconductor) with modern lakehouse consumption patterns</li></ul>
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status. 
Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women&rsquo;s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.
Actual compensation will depend on a candidate&rsquo;s education, experience, skills, and geographic location. The anticipated wage for this position is
$166,500 - $266,200
Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly&rsquo;s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.
#WeAreLilly</div>

Advisor - Scientific Data Engineer

Aircall

<div>
 Aircall is a unicorn, AI-powered customer communications platform used by 22,000+ companies worldwide to drive revenue, resolve issues faster, and scale customer-facing teams. We&rsquo;re redefining customer communications by bringing voice, SMS, WhatsApp, and AI together into one seamless workspace.
 
 
 Our momentum comes from a simple idea: help teams work smarter, not harder. Aircall&rsquo;s AI Voice Agent automates routine calls, AI Assist streamlines post-call work, and AI Assist Pro delivers real-time guidance so people can do their best work. The result is higher revenue, faster resolutions, and teams that scale with confidence.
 
 
 Aircall is headquartered in Paris, our European HQ, with a strong North American presence anchored in Seattle, our North American HQ, and teams across Madrid, London, Berlin, San Francisco, New York City, Sydney, and Mexico City. We&rsquo;ve built a product customers love and a business that&rsquo;s scaling quickly, backed by world-class investors and driven by rapid AI innovation across multiple product lines.
 
 
 At Aircall, you&rsquo;ll join a company in motion. We&rsquo;re ambitious, product-driven, and execution-focused, with visible impact, fast decisions, and real growth.
 
 
 
 How we work at Aircall:
 
 We&rsquo;re customer-obsessed, data-driven, and focused on delivering meaningful outcomes. We value ownership, continuous learning, and thoughtful speed. If you thrive in a collaborative, fast-moving environment where trust and impact matter, you&rsquo;ll feel at home here.
 
 
 
 About The Role
 
 
 
 The Data Engineering team at Aircall works on providing high-quality, reliable, and actionable data. As an AI-first data team, we are currently in a pivotal transition to build a robust semantic layer that will power our AI-first data platform, enabling analytics at speed and democratizing intelligent insights across the company. Some of the key problems we are currently solving include taking charge of data reliability, integrating new sources for raw data ingestion, and building sophisticated data models to power real-time dashboards and predictive analytics.
 
 
 In this role, you will be instrumental in building new datasets for high-impact use cases such as churn prediction and feature adoption, while owning the end-to-end reliability and scalability of our data pipelines. You will work closely with Product and GTM business teams, sitting at the heart of a larger data organization alongside Data Science, Analytics, and Applied Scientists to bridge the gap between raw data and AI-driven decision-making.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design, build and maintain core data infrastructure pieces that allow Aircall to support our many data use cases.
 </li>
 <li>
 Enhance the data stack, lineage monitoring and alerting to prevent incidents and improve data quality.
 </li>
 <li>
 Implement best practices for data management, storage and security to ensure data integrity and compliance with regulations.
 </li>
 <li>
 Own the core company data pipeline, responsible for converting business needs to efficient &amp; reliable data pipelines.
 </li>
 <li>
 Participate in code reviews to ensure code quality and share knowledge.
 </li>
 <li>
 Lead efforts to evaluate and integrate new technologies and tools to enhance our data infrastructure.
 </li>
 <li>
 Define and manage evolving data models and data schemas. Manage SLA for data sets that power our company metrics.
 </li>
 <li>
 Collaborate with applied scientists, data scientists, analysts and other business stakeholders to drive efficiencies for their work, supporting complex data processing, storage and orchestration
 
 
 </li>
 </ul>
 
 A little more about you:
 
 
 
 <ul>
 <li>
 Bachelor's degree or higher in Computer Science, Engineering, or a related field.
 </li>
 <li>
 3+ years of experience in data engineering, with a strong focus on designing and building data pipelines and infrastructure.
 </li>
 <li>
 Proficient in SQL and Python, with the ability to translate complexity into efficient code.
 </li>
 <li>
 Experience with data workflow development and management tools (dbt, Airflow).
 </li>
 <li>
 Solid understanding of distributed computing principles and experience with cloud-based data platforms such as AWS, GCP, or Azure.
 </li>
 <li>
 Strong analytical and problem-solving skills, with the ability to effectively troubleshoot complex data issues.Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.
 </li>
 <li>
 Prior experience designing AI-ready data semantic layer is a major plus, specifically for enabling low-latency, high-fidelity analytics at scale.
 </li>
 <li>
 Experience with data tooling, data governance, business intelligence and data privacy is a plus.
 
 
 </li>
 </ul>
 $130,000 - $200,000 a year
 
 
 This is not including equity and other benefits. The actual salary offered will carefully consider a wide range of factors, including your skills, qualifications, and experience.
 
 
 Why join us?
 
 
 🚀 Key moment to join Aircall in terms of growth and opportunities
 
 
 💆&zwj;&female;️ Our people matter, work-life balance is important at Aircall
 
 
 📚 Fast-learning environment, entrepreneurial and strong team spirit
 
 
 🌍 45+ Nationalities: cosmopolite &amp; multi-cultural mindset
 
 
 💵 Competitive salary package &amp; benefits
 
 
 🏨 Medical, dental, and vision insurance is 100% covered
 
 
 📈 401k plan with company matching!
 
 
 ✈️ Unlimited PTO &mdash; take the time you need to come to work feeling great!
 
 
 ⭐️ Wellness, internet, and childcare reimbursements
 
 
 💚 Generous parental leave policy
 
 
 DE&amp;I Statement:
 
 
 At Aircall, we believe diversity, equity and inclusion &ndash; irrespective of origins, identity, background and orientations &ndash; are core to our journey.
 
 
 We pride ourselves on promoting active inclusion within our business to foster a strong sense of belonging for all. We&rsquo;re working to create a place filled with diverse people who can enrich and learn from one another. We&rsquo;re committed to ensuring that everyone not only has a seat at the table but is valued and respected at it by providing equal opportunities to develop and thrive.
 
 
 We will constantly challenge ourselves to make sure that we live up to our ambitions around diversity, equity and inclusion, and keep this conversation open. Above all else, we understand and acknowledge that we have work to do and much to learn.
 
 
 Want to know more about candidate privacy? Find our Candidate Privacy Notice here.
 
 
 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
</div>

Data Engineer/Senior Data Engineer, Data and Science

Crossing Hurdles

<div>
 
 Crossing Hurdles is a global recruitment firm partnering with leading US-based startups. We are hiring for a
 
 rapidly growing frontier AI infrastructure company
 
 backed by top-tier venture investors and building core systems for the next generation of AI agents. The company is well-capitalized, growing quickly, and building a highly technical team in
 
 San Francisco
 
 to work on some of the most challenging problems in reinforcement learning and AI infrastructure.
 
 
 
 
 
 
 Role Snapshot:
 
 
 
 
 Role:
 
 Member of Technical Staff
 
 
 
 Compensation:
 
 $160K &ndash; $600K + Competitive Equity
 
 
 
 Location:
 
 San Francisco, US | In-person (6 days/week)
 
 
 
 YOE:
 
 0+ years of experience in full-stack or infrastructure engineering, particularly in low-level systems or as a founding engineer
 
 
 
 Benefits:
 
 Competitive Equity + Visa Sponsorship (evaluated case-by-case)
 
 
 
 
 
 
 Why should you consider?
 
 
 <ul>
 <li>
 Work on reinforcement learning environments and infrastructure powering next-generation AI agents.
 </li>
 <li>
 Collaborate with a highly technical team solving complex systems and AI research problems.
 </li>
 <li>
 Build realistic simulation environments, data systems, and tasks for advanced AI training.
 </li>
 <li>
 High ownership in a fast-growing startup backed by top-tier investors.
 </li>
 <li>
 Operate at the frontier of AI development with meaningful real-world impact.
 </li>
 </ul>
</div>

Full Stack Software Engineer

Handshake

<div>
 
 About Handshake
 
 
 
 Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.
 
 
 In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We&rsquo;ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month.
 
 
 
 Why Join Handshake Now
 
 
 
 <ul>
 <li>
 Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel
 </li>
 <li>
 Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world&rsquo;s top educational institutions
 </li>
 <li>
 Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders
 </li>
 <li>
 Build a massive, fast-growing business with billions in revenue
 
 
 </li>
 </ul>
 
 About Handshake AI
 
 
 
 Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale.
 
 
 
 About The Role
 
 
 
 We&rsquo;re hiring a
 
 Software Engineer
 
 to build our Reinforcement Learning Environments (RLE) platform&mdash;the interactive systems where frontier AI models learn to complete real-world work.
 
 
 This role owns meaningful components end-to-end and plays a key part in scaling systems that power model training and evaluation.
 
 
 
 Location:
 
 San Francisco, CA (in-office, 5 days/week)
 
 
 What You&rsquo;ll Do
 
 
 <ul>
 <li>
 Build and scale core components of RLE environments and infrastructure
 </li>
 <li>
 Design and implement backend systems and data pipelines
 </li>
 <li>
 Translate ambiguous product and research needs into production systems
 </li>
 <li>
 Develop modular, reusable workflow domains
 </li>
 <li>
 Improve reliability, observability, and system performance
 
 
 </li>
 </ul>
 What We&rsquo;re Looking For
 
 
 <ul>
 <li>
 2&ndash;4 years of experience in backend, distributed systems, or ML-adjacent infrastructure
 </li>
 <li>
 Strong proficiency in ReactJS and TypeScript
 </li>
 <li>
 Solid experience with relational databases (PostgreSQL) and data modeling
 </li>
 <li>
 Experience with cloud infrastructure (AWS/GCP) and CI/CD
 </li>
 <li>
 Ability to independently drive projects from design to production
 
 
 </li>
 </ul>
 Nice to Have
 
 
 <ul>
 <li>
 Experience with simulation systems or evaluation platforms
 </li>
 <li>
 Exposure to ML systems or working with research teams
 </li>
 <li>
 Experience in fast-moving, operations-heavy environments
 
 
 </li>
 </ul>
 What Success Looks Like
 
 
 <ul>
 <li>
 Owns and delivers key RLE components end-to-end
 </li>
 <li>
 Improves system scalability and developer velocity
 </li>
 <li>
 Enables faster launch of new domains with high-quality data
 
 
 </li>
 </ul>
 
 Perks
 
 
 
 Handshake delivers benefits that help you feel supported&mdash;and thrive at work and in life.
 
 
 The below benefits are for full-time US employees.
 
 
 🎯 Ownership: Equity in a fast-growing company
 
 
 💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching
 
 
 🍼 Family Support: Paid parental leave, fertility benefits, parental coaching
 
 
 💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend
 
 
 📚 Growth: $2,000 learning stipend, ongoing development
 
 
 💻 Office: Commuting support, free lunch, and gym in our SF office
 
 
 🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days
 
 
 🤝 Connection: Team outings &amp; referral bonuses
 
 
 Compensation Range: $157.5K - $175K
 
 
</div>

Software Engineer I, RLE

Explore 220+ Data infrastructure engineer in San Francisco this May. Find roles across top companies and apply now to boost your career.

220 data infrastructure engineer jobs In San Francisco

AI Data Engineer (Agent Platform)

Data Engineer

Data Engineer

Advisor - Scientific Data Engineer

Data Engineer/Senior Data Engineer, Data and Science

Full Stack Software Engineer

Software Engineer I, RLE