CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 38 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences.

We are seeking a strategically-minded, technology-focused, and customer-centric Engineering Manager to lead one of our Infrastructure teams here. You will lead a team responsible for building, operating, and scaling the cloud infrastructure and platform systems that underpin CLEAR’s services, ensuring reliability, performance, and security across our environments.

A successful candidate brings strong experience in cloud infrastructure, distributed systems, and operational excellence, along with a solid foundation in software engineering. You are an effective communicator who can lead complex infrastructure initiatives from inception through delivery, and thrive in fast-paced environments. This role requires a focus on building resilient, scalable systems, driving automation, and leading and developing high-performing engineering teams.

What you'll do:

• Hire, develop, and grow engineering talent through coaching, mentorship, performance management, and career development planning
• Set clear goals and expectations, provide regular feedback, and foster accountability across the team
• Own and execute the roadmap for cloud infrastructure and platform engineering, and reliability initiatives
• Design, build, and operate a scalable, secure, and highly available cloud platform infrastructure
• Drive automation across infrastructure provisioning, deployment, and operations to improve efficiency and reduce manual overhead
• Establish and enforce best practices for system reliability, observability, incident response, and disaster recovery
• Partner with engineering teams to improve deployment pipelines, service operability, and production readiness
• Provide technical leadership, making clear architectural decisions and communicating trade-offs, risks, and impacts
• Own operational excellence through metrics, SLAs/SLOs, and continuous improvement of system performance, reliability, and cost

What you're great at:

• 3+ years of experience managing and developing software engineers, with strong coaching and team leadership skills
• Strong experience with CI/CD systems, infrastructure automation, and release engineering
• Deep knowledge of cloud platforms (e.g., AWS) and distributed systems architecture
• Hands-on experience with Infrastructure as Code (e.g., Terraform, Pulumi)
• Strong expertise in Kubernetes and container orchestration at scale
• Experience designing for high availability, fault tolerance, and operational resilience
• Proficiency in at least one modern programming language (e.g., Python, and or Java) and solid software engineering fundamentals
• Experience with observability tooling (monitoring, logging, tracing) and incident management practices
• Ability to collaborate cross-functionally and influence teams to adopt infrastructure and operational best practices
• Strong interpersonal, communication, and stakeholder management skills
• Curious, proactive, and committed to continuous learning and improvement

How You’ll be Rewarded:

At CLEAR we help YOU move forward - because when you’re at your best, we’re at our best. You’ll work with talented team members who are motivated by our mission of making experiences safer and easier. Our hybrid work environment provides flexibility. In our offices, you’ll enjoy benefits like meals and snacks. We invest in your well-being and learning & development with our stipend and reimbursement programs. 

We offer holistic total rewards, including comprehensive healthcare plans, family building benefits (fertility and adoption/surrogacy support), flexible time off, free OneMedical memberships for you and your dependents, and a 401(k) retirement plan with employer match. 

The total compensation range for this role is $275,000-$350,000, depending on levels of skills and experience.

This range represents the combined base salary, annual bonus incentive, and new hire equity package (in Restricted Stock Units) for this position at CLEAR. Additionally, this role will be eligible for refresh equity grants as part of our ongoing compensation program. Actual compensation will vary based on factors including, but not limited to, location, education, skills, experience, and performance. All stock based compensation will be subject to the terms and conditions of applicable agreements.

CLEAR provides reasonable accommodation to qualified individuals with disabilities or protected needs. Please let us know if you require a reasonable accommodation to apply for a job or perform your job. Examples of reasonable accommodation include, but are not limited to, time off, extra breaks, making a change to the application process or work procedures, policy exceptions, providing documents in an alternative format, live captioning or using a sign language interpreter, or using specialized equipment.

We are committed to a transparent and secure hiring process. All communications related to this role will come directly from a CLEAR employee through valid CLEAR channels (e.g., a valid @clearme.com email address or verified CLEAR LinkedIn profile). We encourage candidates to remain alert to job scams and to report any suspicious activity.

#LI-Onsite

What You Will Do

• Own end-to-end implementations with enterprise customers, from kickoff through production, working through whatever obstacles come up along the way.
• Understand customer pain points deeply and translate them into concrete product solutions, feeding signal back to engineering and product teams.
• Build internal tools and processes that drive efficiency and scalability across the FDE function.
• Collaborate with cross-functional teams including GTM, product, and core engineering to deliver large-scale projects with cross-team dependencies.
• Run on-site workshops, discovery sessions, and technical enablement with enterprise customers.
• Maintain and operate solutions at high scale, ensuring the highest levels of security and reliability for customer deployments.
• Implement identity synchronization and lifecycle management solutions using SCIM, SSO, SAML, and other enterprise standards.
• Work with Infrastructure as Code (Terraform, AWS CloudFormation, Kubernetes) to deliver scalable, high-availability applications.
• Build and maintain high-quality software using TypeScript, Next.js, React, and REST APIs, including direct contributions to the v0 codebase.
• Be a daily practitioner of AI-assisted development: v0, Cursor, Claude, Codex, and whatever comes next.

About You

Core qualifications:

• Power user of AI coding tools. You use v0, Cursor, Claude, Codex, or equivalent daily and have a current, working understanding of the AI coding landscape: agents, MCP, context management, local vs. remote execution.
• Proficient in Next.js, React, and TypeScript. You're comfortable working directly in a production codebase.
• Experience in a GTM-adjacent engineering role, whether as a Forward Deployed Engineer, Sales Engineer, Solutions Engineer, or similar. You know how to navigate a sales cycle without losing your technical integrity.
• Experience working directly with enterprise customers: running discovery, building trust, re-engaging at-risk accounts, and finding internal champions.
• Willingness to travel to customer sites regularly.
• Strong problem-solving skills and the ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders.
• Comfortable working autonomously and making decisions with minimal supervision in a fast-moving environment.

Bonus points:

• Experience with enterprise integration work:
• Accounts: SSO, account provisioning, RBAC configuration and implementation.
• Relationship building: cultivating internal champions, running on-site workshops, re-engaging at-risk customers.
• Security and Legal: translating security requirements, navigating procurement and legal review processes.
• Data chops. Comfortable writing SQL to understand customer health, usage trends, and spot expansion opportunities.
• Familiarity with access control models like RBAC, ABAC, and ReBAC.
• Background in cloud infrastructure and distributed systems (AWS, Kubernetes, Terraform).
• Strong knowledge of security architecture: LDAP, Active Directory, SAML, OAuth2, OpenID Connect.

Benefits

• Competitive compensation package, including equity.
• Inclusive Healthcare Package.
• Learn and Grow: mentorship and access to events that build your network and skills.
• Flexible Time Off.
• Equipment provided, plus a WFH budget to outfit your space.
• Travel covered for customer engagements.

The San Francisco, CA base pay range for this role is $126,000 to $188,000. Actual salary will be based on job-related skills, experience, and location. Compensation outside of San Francisco may be adjusted based on employee location. Total compensation may include equity, a company bonus, or variable pay. Your recruiter can share more details during the hiring process.

Vercel is committed to fostering and empowering an inclusive community within our organization. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Vercel encourages everyone to apply for our available positions, even if they don't necessarily check every box on the job description.

Engineering at Brex

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

As the Engineering Manager for Cloud Infrastructure, you will lead a highly competent team of senior engineers responsible for the foundational AWS ecosystem that powers Brex. Your primary near-term mission will be driving our high-priority Business Continuity and Disaster Recovery (BCDR) initiative to completion, a company-level priority that involves multi-region failover and infrastructure-wide resilience. You will balance people leadership with deep technical involvement, earning the respect of a senior team while improving operational hygiene and cross-functional coordination across the entire engineering organization.

Where you’ll work

This role will be based in our Seattle office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week: Monday, Wednesday, and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Lead and Grow: Manage and support a senior team of 6 ICs, fostering a culture of high ownership, autonomy, and technical excellence.
• Drive BCDR Strategy: Oversee the execution of the multi-year BCDR initiative, ensuring multi-region infrastructure readiness and automated failover capabilities.
• Technical Stewardship: Maintain and scale Brex’s core cloud infrastructure, including Kubernetes (EKS), RDS/Aurora/Postgres, networking (VPC), and AWS service integrations.
• Cross-Functional Collaboration: Partner with product and engineering teams across Brex to drive adoption of new infrastructure capabilities and ensure successful migrations.
• Operational Excellence: Improve team hygiene by establishing and improving best practices for work tracking (Linear), documentation, and incident response.
• Resource Management: Effectively allocate resources to balance critical project delivery with long-term infrastructure stability.

Requirements

• Leadership Experience: 3+ years of experience directly managing software or infrastructure engineering teams.
• Technical Depth: Deep hands-on experience with cloud infrastructure foundations, specifically AWS, Kubernetes, and Postgres.
• Architectural Insight: Proven ability to design and implement complex infrastructure projects such as multi-region deployments or disaster recovery frameworks.
• Collaborative Mindset: Strong communication skills with the ability to influence technical decisions across multiple autonomous teams.
• Analytical Problem Solving: Ability to dive deep into technical issues while maintaining a high-level strategic view of organizational goals.
• Engineering Background: 5+ years of experience in software or systems engineering.

Bonus points

• Experience with Infrastructure as Code tools, specifically Terraform.
• Background in managing cloud infrastructure cost optimization programs.
• Experience with our tech stack components: Go, Kotlin, Python, or Elixir.
• Passion for leveraging AI and LLM-assisted workflows to increase engineering velocity.

Compensation

The expected salary range for this role is $240,000 - $300,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

About the Role

The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.

Within Cloud Inference, the model & inference launch team owns the validation pipeline for our inference server and load balancer on these platforms. We're responsible for every inference change — model launches, performance improvements, safeguard integrations — landing on cloud platforms with correctness, performance, and reliability intact.

This is high-leverage infrastructure work: validation has to be fast and cheap enough to run on the same accelerators that serve customers, trustworthy enough to replace manual checks, and consistent enough that a change working on Anthropic first-party means it works everywhere. This directly determines how fast frontier models and features ship to every cloud platform, and how quickly performance wins reach production — reclaiming capacity at a time when compute is our scarcest resource.

What You'll Do

• Be on the critical path for frontier model launches, bringing up inference for new model architectures and shipping them to cloud platforms in lockstep with our first-party platform
• Work with the core inference team to bring new inference features (e.g. structured sampling, prompt caching, and more) to cloud platforms, owning the platform-specific integration that gets them to production
• Identify and dive deep on the gaps that make inference behave differently across first-party and CSPs — config drift, observability, deployment patterns, hard cross-platform bugs — and fix them at the source rather than building platform-specific workarounds
• Design, build, and own the CI/CD infrastructure for the inference server and load balancer across cloud platforms, with shadow traffic, performance baselines (throughput and latency), and correctness checks that catch regressions before production
• Drive down merge-to-production cycle time by making validation faster, more parallel, and cost-effective enough to run on the same constrained accelerator pool that serves customers, without trading away reliability 
• Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads

You May Be a Good Fit If You:

• Have a strong interest in LLM serving; prior inference or ML experience is not required 
• Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
• Have a track record of building automation or test infrastructure that measurably improved release velocity or reliability
• Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration
• Thrive in cross-functional collaboration with both internal teams and external partners
• Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
• Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description

Strong Candidates May Also Have Experience With:

• LLM inference optimization, batching, and caching strategies
• Capacity-constrained scheduling or shared-resource test infrastructure
• Solid understanding of multi-region deployments, request routing, load balancing, global traffic management
• Working with CSP partner teams to scale infrastructure across multiple platforms, navigating differences in networking, security, privacy, and managed service
• Proficiency in Python or Rust

Engineering at Brex

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

As a Security Operations Engineer at Brex, you will focus on preventing, detecting and responding to security threats across Brex's corporate and cloud environments. You will use existing systems and develop tools to improve our security capabilities. Our team is responsible for functions across corporate security, detection & response and infrastructure security domains; and we perform systems engineering and automation to support those functions. 

Security Operations is part of our wider Trust & IT organization which means you will have the opportunity to work closely with Application Security, Corporate Engineering, GRC and IT and to improve security configurations, drive positive employee behaviors and generally work to prevent events from becoming incidents. You will also help build and maintain our team’s open source project Substation and have the opportunity to contribute to the Brex Tech Blog. You’ll be part of a team that actively contributes to the wider security community and has a commitment to mentorship and engineering excellence.

We’re looking for individuals with a strong background and interest in detecting, responding to, and resolving security incidents and security challenges. You should be comfortable dealing with lots of moving pieces, changing priorities, and new technologies, while having a keen eye for detail. Most importantly, you should be enthusiastic about working with a variety of backgrounds, roles, and people across Brex. Building a world-class financial service requires world-class security.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Work on a highly cross-functional team to prevent, detect and respond to security threats across Brex's corporate and cloud environments
• Perform security incident response, investigation, remediation, and documentation, participate in periodic threat hunting and security exercises
• Leading, scoping and building features, participate in designing, and maintaining tools and systems which support the team’s domains – corporate security, detection & response and infrastructure security 
• Collaborating and partnering with engineering and operations teams to drive remediation of security issues, while balancing prioritization of those security issues within SLA and teams’ respective backlogs
• Caring about secure system design, valuing building things correctly, an understanding of a MVP approach and an empathetic mindset when working with others

Requirements

• Bachelor’s degree in Computer Science, Engineering or related field OR equivalent training / fellowship OR 5+ years work experienceExperience working in a corporate security, detection & response or infrastructure security role with responsibilities for security alert triage and security incident response 
• Familiarity with CI/CD systems and DevOps workflows (e.g. Buildkite, Flux, Git, Terraform) in cloud environments (e.g. AWS, Azure, GCP)
• Experience with deploying and maintaining some of the security services and tools owned by the team (e.g. - SIEM, data pipelines, SOAR, domain monitoring, endpoint tooling, email protection tooling, cloud security tools)
• While not primarily a development role, the team develops and maintains tools written in Go and Python, so experience with coding is required
• You thrive in a collaborative environment filled with a diverse group of people with different expertise and backgrounds. We currently have around 30 nationalities represented with more than ½ the company working in a country different from the one they grew up in.

Bonus points

• Proficiency with Go and other programming languages 
• Experience with securing distributed systems in AWS, cloud and Kubernetes environments
• Contributions to the wider technical community (open source, public research, mentorship, community organizing, blogging, presentations, etc)

Compensation

The expected salary range for this role is $192,000 - $240,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Code and Theory is seeking a senior cloud engineer who wants to own the full technical lifecycle of enterprise client deployments — from assessing a client's existing infrastructure and designing the integration architecture, to provisioning the environment and keeping it running in production. This is a hands-on role that also requires real client engagement: you will sit in technical working sessions, work directly with client DevOps teams, and be the person who translates security and compliance requirements into concrete infrastructure decisions.

You will be working on a platform that connects our AI product to enterprise marketing environments across different cloud providers. Each client brings its own infrastructure, data stack, and security perimeter. Your job is to figure out how to connect to it, build the integration reliably, and hand it off in a state that can be operated and maintained over time.

WHAT YOU'LL DO

• Assess each client's cloud infrastructure, data stack, and security perimeter before any build starts — translate findings into a concrete integration plan
• Design and provision client environments using Terraform — networking, IAM, container orchestration, managed storage, and secrets management across GCP, AWS, or Azure depending on the client
• Deploy and operate LLM inference pods in client cloud environments — managing API integration, rate limits, latency, and failure handling without needing a data scientist in the room
• Build and maintain integration layers that connect client data sources to the AI layer — you own the plumbing that makes inference useful; the data science team owns what runs on top of it
• Deploy and maintain containerized workloads via Helm — orchestration, ETL workers, and AI inference pods running inside the client's cloud perimeter
• Own data pipeline deployments end to end — scheduling, pagination, retry logic, and rate-limit management against client API gateways
• Manage distributed ETL jobs at scale — JSON flattening, schema enforcement, and structured output delivery
• Enforce data residency requirements — raw data stays inside the client's environment, only structured output leaves to our shared infrastructure
• Serve as the primary technical contact for each client's DevOps and infrastructure teams throughout the engagement
• Lead technical working sessions with client teams — validate configurations, confirm IAM and credential models, review cluster specs before deployment
• Triage and resolve pipeline and infrastructure failures across multiple client environments simultaneously
• Implement container security standards — non-root execution, read-only filesystems, startup integrity hashes, tamper protection
• Mentor junior and mid-level engineers and contribute implementation patterns to the shared playbook after every client engagement

WHAT YOU'LL NEED

• 6+ years of cloud engineering experience — production experience on at least two of GCP, AWS, or Azure, and willing to operate across all three depending on client environment
• Deep Terraform experience — you have provisioned multi-environment, multi-tenant production infrastructure from scratch, not just applied existing configurations
• Comfortable with Kubernetes and Helm in production — deploying, debugging, scaling, and securing containerized workloads, not just running them
• Have run data pipelines in production — you know what breaks, how to recover, and how to build retry and backoff logic that actually holds up
• Hands-on experience with distributed processing at scale — not just theoretical knowledge
• Enterprise API integration experience — OAuth 2.0, API key management, rate limiting, API gateways — end to end
• Solid security fundamentals — container hardening, credential management, and data residency enforcement in environments where it actually matters
• Have worked directly with client or customer engineering teams — comfortable leading technical conversations with enterprise DevOps and infrastructure teams, not just supporting them
• You write things down — runbooks, integration notes, playbook contributions. The next engineer should be able to operate what you built
• Hands-on experience integrating LLM APIs (Anthropic, OpenAI, or equivalent) into production pipelines — not as an end user, but wiring inference into systems that run at scale across real client environments

NICE TO HAVE

• Experience with:
  • LLM inference infrastructure
  • Marketing technology stacks (DAM, CDP, CRM)
  • Multi-tenant client environments
• A cloud certification (AWS Solutions Architect, GCP Professional Cloud Architect, or Azure equivalent)
• Agency, consultancy, or product company background serving multiple enterprise clients simultaneously

ABOUT US

Born in 2001, Code and Theory is a digital-first creative agency that sits at the center of creativity and technology. We pride ourselves on not only solving consumer and business problems, but also helping to establish new capabilities for our clients. With a global client roster of Fortune 100s and start-ups alike, we crave the hardest problems to solve. We have teams distributed across North America, South America, Europe, and Asia. The Code and Theory global network of agencies is growing and includes Kettle, Instrument, Left Field Labs, Create Group, Current, and TrueLogic.

Striving never to be pigeonholed, we work across every major category: from tech to CPG, financial services to travel & hospitality, government and education to media and publishing. We value the collaboration with our client partners, including but not limited to Adidas, Amazon, Con Edison, Diageo, EY, J.P. Morgan Chase, Lenovo, Marriott, Mars, Microsoft, Thomson Reuters, and TikTok.

The Code and Theory network is comprised of nearly 2,000 people with 50% engineers and 50% creative talent. We’re always on the lookout for smart, driven, and forward-thinking people to join our team.

The target range of base compensation for this role is $110,000 - $150,000. Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, and location.

What you’ll do

As a Staff Software Engineer on the Identity & Access Management (IAM) team, you will be a primary architect of CoreWeave’s IAM strategy as we rapidly expand the platform. You will leverage your deep expertise in identity systems to design, extend, and harden a platform that secures our high-performance cloud infrastructure. This is a high-impact leadership role where you will balance rapid execution with the long-term technical vision necessary to meet the demands of our global enterprise customers.

About the role

• Technical Strategy & Vision: Partner with Product and Engineering Leadership to translate complex requirements into a multi-year technical roadmap that balances immediate business needs with long-term architectural integrity
• System Architecture: Lead the design and implementation of high-throughput, low-latency distributed systems for authentication and authorization across all CoreWeave services
• Platform Evolution: Architect customer-facing experiences for identity lifecycle management, IdP integration (SAML/OIDC), and granular permissioning models
• Engineering Excellence: Champion a security-first mindset across the organization, establishing rigorous standards for code quality, design reviews, and threat modeling
• Operational Leadership: Elevate the team’s operational maturity by defining SLOs, enhancing deep-stack observability, and driving automation to eliminate systemic toil
• Technical Mentorship: Act as a force multiplier by mentoring Senior engineers and fostering a culture of continuous learning and high-performance engineering
• Cross-Functional Influence: Drive alignment on critical security initiatives across the broader engineering organization, articulating complex technical trade-offs to stakeholders

Who you are

• 10+ Years of Experience building and operating large-scale distributed systems in a production environment using one or more of Go, TypeScript, or React
• 5+ Years of IAM Domain Expertise: Proven track record of developing identity products and a deep mastery of standards including OIDC, OAuth2.0, SAML, and JWT
• Technical Leadership: Demonstrated experience leading large, cross-functional projects from inception to planet-scale deployment with measurable business impact
• Cloud-Native Mastery: Deep understanding of Kubernetes, microservices architecture at scale, and advanced CI/CD patterns
• Enterprise Security Acumen: Solid knowledge of the security, compliance (SOC2, HIPAA, etc.), and governance needs of sophisticated enterprise customers
• Strategic Communication: Superb ability to synthesize ambiguous requirements into clear technical designs and communicate trade-offs to both executive and technical audiences
• Analytical Problem Solving: Expert-level ability to debug complex, intermittent issues within distributed environments

Preferred

• Architectural Transformation: Experience leading the decomposition of monolithic architectures into high-performance microservices
• AI-Augmented Development: Familiarity with leveraging AI agents (e.g., Claude, Cursor) to accelerate the software development lifecycle
• Emerging Tech Knowledge: Familiarity with AI/ML workloads, GPU-based infrastructure, and the unique security challenges of MLOps at scale
• Policy-as-Code: Experience with modern authorization frameworks such as Open Policy Agent (OPA) or Cedar

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk. 

• You love to solve complex problems and build high-scale, low-latency distributed systems.
• You’re curious about how to evolve cloud platforms and scale infrastructure globally for the next generation of AI workloads.
• You’re an expert in one or more preferred programming languages (Go, TypeScript, Python), and have deep technical knowledge of distributed systems.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The base salary range for this role is $188,000 to $275,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

What You’ll Do

As a Senior Software Engineer on the Identity & Access Management (IAM) team, you will play a key role in designing, building, scaling, and maintaining CoreWeave’s rapidly expanding IAM platform. You will leverage your experience in distributed systems to design, extend, and harden a platform that secures our high-performance cloud infrastructure. You’ll be working at the intersection of design, developer experience, and platform architecture to help scale our services to the next order of magnitude. Here are just a few of the interesting and exciting things you’ll be doing:

• Architect and build high-scale, low-latency distributed systems that power CoreWeave’s identity, authentication and authorization services
• Design and implement customer-facing and internal APIs and backend services that underpin our IAM platform
• Optimize system performance to ensure that services remain highly available and performant under unpredictable load patterns
• Collaborate cross-functionally with stakeholders across the business, including product managers, designers and TPMs, to shape the team’s strategy and roadmap
• Drive operational excellence by participating in on-call rotations and building automated tooling for monitoring, alerting, and incident response
• Demonstrate and shape best-practices in software engineering by embracing AI for development, insisting on maintainable and testable code, and participating in thorough code reviews
• Work with incredible people in a supportive, iterative, high-trust, agile environment

Who You Are

• Experience: Minimum of 5 years of professional experience developing, operating and maintaining backend services in a production environment
• Programming: Strong proficiency developing software in one or more of our preferred languages (Go, TypeScript, Python)
• Distributed systems: Knowledge of microservices architecture, RESTful/gRPC API design, and asynchronous messaging patterns
• Observability: Fluency with best practices in observability (logging, metrics, dashboards, alerting)
• Database design:  Solid understanding of relational databases, schema design, and SQL
• Testing and quality: Strong commitment to automated testing (unit, integration, and E2E) and CI/CD pipelines
• Ownership: Demonstrated ownership of code quality, performance, and maintainability from development through production
• Security: Experience with authentication, authorization and security best practices
• Problem solving: A proven track record of debugging complex performance bottlenecks and distributed system failures in a production environment
• Communication: Excellent verbal and written communication skills, able to work effectively with both technical and non-technical team members

Preferred

• Experience with Kubernetes and a conceptual understanding of its major components.
• Experience building reliable and scalable platform services that process large amounts of data.
• Experience developing identity products on top of standards including OIDC, OAuth2.0, SAML, and JWT
• Experience managing cloud infrastructure (AWS, GCP, etc.)
• Familiarity with Infrastructure-as-Code tools and practices

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk. 

• You love to solve complex problems and build high-scale, low-latency distributed systems.
• You’re curious about how to evolve cloud platforms and scale infrastructure globally for the next generation of AI workloads.
• You’re an expert in one or more preferred programming languages like Go, TypeScript, or Python, and have deep technical knowledge of distributed systems.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The base salary range for this role is $165,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

The Security Products organization at CoreWeave builds the identity, encryption, and self-managed security integrations that protect AI workloads and data across our cloud platform. If you are passionate about building foundational security primitives that enable enterprises and the top AI labs in the world to deploy regulated and security‑sensitive workloads at extreme scale, this is the team to join!

About the role

CoreWeave is seeking a Staff or Principal Engineer for our Security Products team to lead the technical direction and implementation of encryption and key lifecycle management  In this role, you’ll design and evolve the key lifecycle management, encryption control planes, algorithm/library selection, and systems integrations that allow CoreWeave customers to deploy sensitive, high security AI workloads and data. You’ll partner closely with teams across CoreWeave to develop customer-driven cryptography technology. Your day‑to‑day will blend hands‑on system design and coding with cross‑team technical leadership, design reviews, and roadmap shaping for Security Products.

In this role, you will:

• Lead the design and evolution of encryption and key lifecycle management products.
• Manage encryption and cryptography technology development for services within our Cloud Platform, particularly those for high security and highly regulated customers.
• Design and build deep integrations between our Cloud Platform and external key sources (eg, HashiCorp Vault, AWS KMS, HSMs).
• Collaborate with other product engineering teams to support the safe use of multicloud key management technology.
• Partner with IAM to define unified authorization patterns and policy models for key management APIs with consistent semantics across the resource hierarchy.
• Establish SLIs / SLOs for Remote Key Encryption (RKE) and related services, including availability, latency, and durability guarantees for key retrieval and encryption operations.
• Partner with the Security Engineering team on threat modeling and corporate strategy to enable the most sensitive AI workloads in the world to be deployed on CoreWeave's infrastructure.
• Author and review detailed technical designs and RFCs for new RKE capabilities, mentor other engineers on the team, and provide technical leadership across Security Products and adjacent organizations.

Who You Are

• 8+ years of experience building and operating distributed backend systems in production, including ownership of reliability and security outcomes for critical services.
• Deep experience with encryption at rest and key management systems, including envelope encryption patterns, key hierarchies and secure key lifecycle management.
• Hands-on experience integrating with at least one major KMS or secrets manager (e.g., AWS KMS, HashiCorp Vault, Azure Key Vault, GCP KMS, HSMs), including designing APIs and workflows around those systems.
• Strong proficiency in a systems programming language such as Go (preferred) or Rust, with experience building networked services (gRPC / REST) in a Linux / Kubernetes environment.
• Solid understanding of applied cryptography concepts relevant to data‑at‑rest protection (AES‑GCM/CTR, key wrapping, KDFs, randomness requirements, envelope encryption, and key separation) with the ability to reason about threat models and failure modes with Security partners.
• Experience designing and operating multi‑tenant services with strong isolation and authorization semantics across customers and internal tenants.
• Demonstrated track record of leading cross‑team technical initiatives, driving projects from problem statement through rollout, alignment, and operational readiness.
• Strong operational experience defining SLIs / SLOs, building dashboards and alerts, and partnering with SRE / Production Engineering on incident response and post‑incident improvement.
• Excellent written and verbal communication skills with the ability to produce clear, opinionated design docs that influence Senior Engineers, PMs, and Security stakeholders through context setting and sound technical judgment

Preferred (if applicable)

• Prior experience designing or implementing remote or externalized key management for cloud storage, databases, or filesystems (e.g., BYOK/BYOKMS, customer‑managed keys, envelope encryption for S3‑like object storage).
• Experience with hardware‑backed key management (HSMs) and cryptographic compliance regimes (FIPS 140‑2/3, PCI, HIPAA, FedRAMP Moderate+, or similar) and how they shape system design.
• Familiarity with IAM policy models (RBAC / ABAC, OpenFGA, OPA/Rego, etc.) and how to integrate fine‑grained authorization into security‑sensitive APIs.
• Experience extending encryption and key management across multiple storage domains (object storage, block/file storage, databases, control plane state like etcd) in a coherent way.
• Background working in security‑sensitive or regulated environments where auditability, segregation of duties, and key custody requirements are critical.
• Contributions to open source cryptography, security tooling, or KMS/client libraries.
• Previous US/NATO federal cryptographic security experience is ideal but not necessary. 

Wondering if you’re a good fit?

We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• You care deeply about getting the cryptographic and operational details right, and you’re comfortable saying “no” to shortcuts that weaken security or key custody guarantees.
• You’re excited by the challenge of building foundational security primitives that other product teams and large enterprises will build on for years.
• You enjoy working at the intersection between Platform, Storage, IAM, and Security Engineering, and you can translate between those domains without losing the plot.
• You’re skilled at turning complex requirements for highly regulated customers into simple, reliable, well‑documented APIs and workflows.
• You’re comfortable operating in a fast‑moving environment, iterating quickly while still holding a high bar for design review, testing, and safe rollout of security‑sensitive changes.

The base salary range for this role is $206,000 to $303,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

SeatGeek believes live events are powerful experiences that unite humans. With our technological savvy and fan-first attitude we’re simplifying and modernizing the ticketing industry.

By catering to both consumers and enterprises, we’re powering a new, open entertainment ecosystem where fans have effortless access to experiences, and teams, venues, and shows have seamless access to their audiences. Because everyone should expect more from ticketing.

SeatGeek has an ever-evolving product that's reshaping the way the ticketing industry works. You’ll join the team responsible for ensuring SeatGeek.com is fast, reliable, and delivering joy to all of our fans.

What you'll do

• Work with the SeatGeek design team and product managers to bring ideas to life to delight fans
• Bring a passion for product to mentor and grow web engineers across the organization
• Contribute to increasing the maturity of our front end tech strategy and stack

What you have

• 5+ years of professional experience in frontend software engineering, having led product initiatives end-to-end in recent years 
• TypeScript/JavaScript: You have an exceptional grasp of the language. You keep up with the latest spec and look for every opportunity to use new features. You're familiar with at least one modern framework and client side rendering technique. We use TypeScript, React, and Next.js to create our user interfaces, although specific knowledge of those is not a prerequisite.
• UI & Product Instincts: You have feelings about how a web page should look and feel, care about the nuances of how users will work with the product you're building, and aim to build inclusive and accessible experiences. We don't expect you to be a visual designer, but we're looking for someone who can build on the work of our experienced design team.
• Architecture and Performance optimization: You are comfortable going deeper into the stack to untangle caching inefficiencies, and troubleshoot across a wide array of distributed systems that make up a dynamic web application. You know how to use monitors and testing to know if changes improved or degraded the experience. You know how to architect for performance and maintainability.
• Adaptability: You have comfort working full stack in Python when needed to get things done.  You have some experience with design tools like Figma or Sketch. If you've never worked with any of these in your life but want to fearlessly dive in, please still apply.

Our stack

You do not need experience with any of these, but we thought you might be curious. What we care about is your experience, skills, and approach to problem solving. Tools can be learned.

• Languages: Typescript, Python
• Libraries / Frameworks: Next.js, React
• Infrastructure / Tools: AWS, K8s, Fastly, Datadog, Mixpanel, Eppo

Perks

• Equity stake
• Discretionary annual bonus
• Flexible work environment, allowing you to work as many days a week in the office as you’d like or 100% remotely
• A WFH stipend to support your home office setup
• Unlimited PTO
• Up to 16 weeks of fully-paid family leave 
• 401(k) matching 
• Student loan matching program
• Health, vision, dental, and life insurance
• Up to $25k towards family building, reproductive health services and Gender-affirming care
• $500 per year for wellness expenses
• Subscriptions to Headspace (meditation), Headspace Care (therapy), and One Medical
• $120 per month to spend on tickets to live events
• Annual subscription to Spotify, Apple Music, or Amazon music

The salary range for this role is $144,000 - $209,000 USD. This role is equity eligible. In addition, you may receive a discretionary annual bonus based on individual and company performance. Actual compensation packages within that range are based on a wide array of factors unique to each candidate, including but not limited to skill set, years and depth of experience, certifications, and specific location.

SeatGeek is committed to providing equal employment opportunities to all employees and applicants for employment regardless of race, color, religion, creed, age, national origin or ancestry, ethnicity, sex, sexual orientation, gender identity or expression, disability, military or veteran status, or any other category protected by federal, state, or local law. As an equal opportunities employer, we recognize that diversity is a positive attribute and we welcome the differences and benefits that a diverse culture brings. Come join us!

To review our candidate privacy notice, click here.

Hi, we're Oscar. We're hiring an Applied AI Engineer to join our AI team.

Oscar is the first health insurance company built around a full stack technology platform and a focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role

Join Oscar’s AI team to build and launch transformative AI-powered products that redefine the healthcare experience for millions. As an Applied AI Engineer, you’ll take end-to-end ownership of high-impact projects—conceiving, prototyping, and deploying generative AI solutions that solve real-world problems across the healthcare ecosystem.You’ll work alongside a world-class team of engineers and data scientists, rapidly iterating on ideas and shipping production-ready applications that drive measurable business and user outcomes. You’ll have the autonomy to identify opportunities, experiment with the latest AI models and techniques, and deliver solutions that streamline operations, improve patient experiences, and move the needle for Oscar and our members.

You will report to the Sr. Director, AI.

Work Location: This position is based in our New York City office, requiring a hybrid work schedule with 3 days of in-office work per week. Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $163,944 - $236,911 per year. You are also eligible for employee benefits, participation in Oscar’s unlimited vacation program, company equity grants, and annual performance bonuses.

Responsibilities

• Lead the design, development, and deployment of AI-driven products and features, from zero-to-one prototypes to robust production systems.
• Collaborate cross-functionally with product, design, and business teams to deeply understand user needs and deliver solutions that move key metrics.
• Rapidly experiment with new models, techniques, and tools (including LLMs, RAG, and agentic workflows), iterating based on data and user feedback.
• Build and scale full-stack applications and intelligent agents that automate complex healthcare workflows and deliver seamless user experiences.
• Stay on the cutting edge of the AI ecosystem, evaluating and integrating emerging technologies to keep Oscar at the forefront of healthcare innovation.
• Contribute to Oscar’s AI strategy and technical vision, helping shape the future of healthcare through technology.
• Other duties as assigned

Qualifications

• 7+ years of professional experience in software engineering, data science, or a related field, with a track record of impactful accomplishments
• Strong Python programming skills
• Experience solving complex, ambiguous problems 
• Experience designing and analyzing experiments or evaluations
• Experience or an interest in prototyping full-stack applications

Bonus Points

• Experience with the healthcare industry. Familiarity with claims or clinical data.
• Degree in math, statistics, data science, or engineering.
• Our ideal candidate is a data scientist with an engineering background, an engineer with a data science background, or a founder-type who combines product thinking, rapid prototyping, and hands-on coding to deliver real-world impact.
• Experience with NLP, neural networks, transformers, and modern AI frameworks.
• Knowledge of containerization and deployment tools (e.g., Docker, Kubernetes) or full-stack development (e.g., React, Golang).
• Experimental mindset: comfort with testing hypotheses and iterating on failures.

About Role

Clockwork is seeking a sales-savvy individual with extensive technical expertise in AI networking to fill our Senior Solutions Engineer position. Do you thrive in a fast-paced, dynamic environment? Utilize your networking expertise, systems engineering background, and consultative skills to partner with our sales team throughout the entire customer journey—from understanding requirements and delivering compelling technical presentations and demos to conducting proof-of-concept (PoC) evaluations and overseeing complex software deployments.

What you will do

• Collaborate closely with customers to understand their unique business needs and create, prototype, and deploy tailored solutions that align with their requirements.
• Lead proof of concept evaluations to showcase the value of Clockwork's solutions within customer environments.
• Provide technical leadership during customer meetings, presentations, and workshops, addressing any technical queries or concerns that arise.
• Work closely with Clockwork's sales team to complete PoC evaluations and close deals.
• Collaborate with product and engineering teams, and identify opportunities for product enhancement.
• Offer valuable insights on product features, functionality, and performance, contributing to discussions about product strategy and architecture.
• Stay abreast of the latest developments and trends in AI networking, Kubernetes, and cloud computing, sharing your thought leadership with customers and internal stakeholders.
• Represent Clockwork at conferences and industry events, with occasional travel as required.

Experience/skills you bring to the position

• 5+ years in a solutions architect or engineering role, preferably within cloud or AI infrastructure domains.
• Previous pre-sales experience, including POCs, with client stakeholders, including senior technical staff and management.
• Hands-on experience with cloud platforms (AWS, GCP, Azure, OCI).
• Strong understanding of Kubernetes and container orchestration.
• Familiarity with GPU infrastructure and related technologies.
• Extensive knowledge of networking protocols.
• Excellent communication and relationship-building abilities, with a customer-centric mindset.
• Demonstrated ability to troubleshoot complex technical issues and provide effective solutions.
• A degree in computer science, electrical engineering or related field.
• Proficiency with Python, SQL, and Linux (Golang, C, C++, and Java are a plus).

Compensation for this position will vary based on the skills and experience you bring, as well as internal equity considerations. For candidates hired at the posted level, the expected base salary range is $170,000 - $250,000. In addition to cash compensation, this role is eligible to participate in the company’s equity program, which may include stock options granted in accordance with the company’s equity plan and subject to approval and applicable vesting schedules.

Enjoy

• Challenging projects.
• Competitive compensation.
• A great benefits package.
• A friendly and inclusive workplace culture.
• Catered lunches.

The Role

We are seeking a Software Engineer to join the Precompute team within our Core Product Engineering organization.

Our team is focused on building high-performance data and compute infrastructure that powers large-scale analytics, APIs, and downstream product experiences for our global customer base of Financial Advisors and Wealth Managers.

We partner closely with a world-class team of engineers, designers, and product managers, and put system performance, scalability, and reliability at the forefront of every initiative.

Our platform is rapidly evolving to support increasingly complex workloads, and as we modernize our architecture, we are enabling new capabilities through high-throughput data pipelines, efficient compute primitives, and flexible APIs. We pride ourselves on delivering robust, scalable, and highly performant systems.

The Precompute team builds and operates the foundational computation layer that accelerates financial analytics across the platform, with a strong emphasis on vectorisation, parallelism, and distributed processing. Our systems form the backbone of how data is processed and served at scale.

Addepar takes a market-based approach to pay. A successful candidate’s starting pay will be determined based on the role, job-related skills, experience, qualifications, work location, and market conditions. The range displayed on each job posting reflects the minimum and maximum target base salary for roles in Colorado, California, and New York.

The current range for this role is $107,000 - $168,000 (base salary) + bonus + equity + benefits. 

Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Additionally, these ranges reflect the base salary only, and do not include bonus, equity, or benefits.

Applicants must be legally authorized to work in the United States for any employer without requiring current or future visa sponsorship (for example, employment-based visas such as H-1B, F-1/OPT, or similar), and must be authorized to begin work in the U.S. on their first day of employment.

What You’ll Do

Work with teams across the organisation to:

• Develop and implement core computation and data processing capabilities that align with our product vision within a multi-functional team
• Enhance the performance and scalability of our computation platform, processing large volumes of financial data efficiently across distributed systems
• Develop systems that leverage vectorised execution, parallelism, and elastic infrastructure to optimise throughput and latency

Who You Are

• Comfortable working independently, with a bias for action
• Thrives in ambiguous spaces where there isn’t a clear solution
• Enjoys digging into new problems and unfamiliar codebases
• Excels at written and verbal communication
• 3+ years of backend software engineering experience
• Proficiency in developing with server-side OO languages like Java
• Proficiency with Linux
• Familiarity with infrastructure components such as CI/CD, monitoring, logging, containers, Kubernetes, and infrastructure-as-code
• Familiarity with HTTP, developing REST and web APIs

Mark43’s mission is to empower communities and their governments with new technologies that improve the safety and quality of life for all. We build powerful, scalable, and elegant software that sets a new standard for the tools upon which our first responders rely. Our users are diverse, and we are therefore committed to embracing diversity of thought and experience within our team.

Mark43 is seeking an Integration Analyst to join our Global Services team. This role will be critical to the success and scalability of our customer deployments across the country. The Mark43 Integration Analyst is passionate about implementing the next generation of law enforcement technologies.

You will work on a customer-facing team to assist with the implementation of technical services for public safety agencies. Public safety has a complex technical ecosystem, and you will play a key role in analyzing our customers’ technical landscapes, processes, and policies in order to recommend services, such as interfaces that create efficiencies for Mark43 and its customers. You will work closely with multiple stakeholders, including customers, third-party vendors, and Mark43 engineering teams, to ensure timely delivery of services that bring value to our customers.

This role requires sharp attention to detail, strong organizational skills, an interest in working directly with customers, and a knack for supporting law enforcement users with revolutionary software. Members of our current team have backgrounds in consulting, technical project management, and experience with large SaaS deployment projects.

What you can expect to work on:

• Assist key stakeholders, such as customers, third-party vendors, and Mark43 engineering teams, through the different stages of technical implementation, including requirements gathering, solutioning, documentation, mapping, configuration, and user acceptance testing.
• Track technical project schedules with stakeholders, help identify schedule risks, and support Implementation Managers with mitigation strategies.
• Configure, schedule, and maintain containerized software across a multi-cloud environment.
• Update external-facing technical documentation to educate stakeholders on Mark43 technical solutions.
• Work towards a worthwhile mission with a team of friendly and intelligent coworkers.

What we expect from you:

• 1-3 years' experience in an Integration Analyst, Implementation Specialist, Technical Analyst, Technical Project Management, or IT support role at a growing company.
• Passion for supporting law enforcement, first responders, and other government agencies.
• Experience in a customer-facing role, preferably in project management, training, customer support, and/or feedback collection.
• Strong organizational skills and ability to multitask.
• Excellent written and oral communication skills.
• Ability to work independently and towards a deadline with minimal oversight.
• Ownership over your own work and a commitment to every part of a task, from big picture to small details.
• An attitude that is self-motivated, humble, detail-oriented, and committed to quality.
• Knowledge of API Integrations, XML, JSON, and Kubernetes.
• Knowledge of SQL.
• Strong troubleshooting skills, the ability to read technical logs.
• Basic understanding of Linux systems.

What you can expect from us:

• Real opportunity for career growth in an environment where your achievements will be celebrated.
• Building mission-critical and socially responsible software to enable first responders to better serve their communities.
• Constant collaboration with numerous Mark43 teams, including Customer Success, Technical Support, Product, and Engineering.
• A team that respects and embraces your ideas and expertise.
• Coworkers that are motivated by pursuing excellence, rather than the prospect of personal gain.
• A workplace dedicated to supporting and bettering public safety and government agencies.

Come Work With Us:

Metropolitan Commercial Bank (“MCB” or the “Bank”) is a New York City–based, full-service commercial bank providing tailored banking solutions to businesses, institutions, and individuals. Founded in 1999, MCB operates banking centers in Manhattan and Boro Park, Brooklyn, within New York City, as well as in Great Neck on Long Island, New York, and Lakewood, New Jersey. The Bank recently expanded to Miami, Florida with their newest Brickell banking center.

Metropolitan Commercial Bank offers a comprehensive suite of commercial, business, and personal banking products and services to small businesses, middle-market and corporate enterprises, private and public institutions, municipalities, and local government entities.

The Bank has earned national recognition for its financial performance, innovation, and strategic growth. The Bank was named one of Newsweek’s Best Regional Banks in 2024 and 2025. Additionally, MCB recently received Editor’s Choice recognition at the Banking Tech Awards USA for Digital Onboarding & Omnichannel Banking and in 2026, the Bank earned Great Place To Work certification and received the Web Award Standard of Excellence for MCBankNY.com.

We are a client-focused organization that values technological innovation and excellence. A strong technical mindset, AI fluency, and adaptive skills are essential for our employees to effectively contribute to our mission and drive our success. We foster human–AI teaming and strong governance to ensure technology is used responsibly and in alignment with Bank policies and procedures. For more information about the Bank, please visit the Bank’s website at MCBankNY.com.

Position Summary:

Metropolitan Commercial Bank (the “Bank”) is seeking a VP-level AI/ML Engineer to deploy AI solutions at enterprise scale, with a strong emphasis on Large Language Model (LLM) applications and modern MLOps & AIOps practices. This role sits at the intersection of data science and software engineering, reporting to the manager of the IT Application Development and Support team and working closely with the Chief Artificial Intelligence Officer, transforming innovative AI prototypes into robust, scalable production systems. The AI/ML Engineer will lead the deployment of high-impact AI capabilities (e.g., generative AI systems, personalization engines, automation tools) and ensure scalable AI platforms that deliver real-world value. The role also includes designing, constructing, and maintaining the Bank’s AIOps solution, with Snowflake as the primary ML platform (e.g., Snowpark Python, UDFs/UDTFs, Tasks/Streams, and Snowflake-native ML).

Standard 4-day in-office requirement, 1 day remote (of your choosing)

Essential Functions & Responsibilities 

Production Architecture & AIOps

• Establish and enforce architecture standards for production AI systems, including data pipelines, model serving infrastructure, and real-time inference services.
• Implement AIOps/MLOps pipelines for CI/CD of ML models, model governance, monitoring, and lifecycle management.
• Design and maintain scalable software applications with integrated AI/ML capabilities.
• Develop software architecture and design patterns to ensure performance and scalability.
• Write clean, maintainable code in general-purpose programming languages (Python, Java, C, C++, Go).
• Implement and manage data pipelines for preprocessing and transforming data for AI/ML models.
• Integrate AI/ML models into production environments and optimize for reliability and scalability.
• Apply Site Reliability Engineering (SRE) principles and implement monitoring and alerting solutions.
• Conduct code reviews and provide technical guidance to junior developers.
• Stay current with advancements in software engineering and AI/ML technologies.
• Adhere to agile and lean software development best practices.
• Thoroughly document all developed models and processes according to relevant policies and standards.
• Support the production environment by either resolving technical or functional issues, in line with the procedures defined by the Bank.

Cross-Functional Collaboration

• Partner with data scientists, AI scientists, product managers, data engineers, DevOps, and business stakeholders to operationalize AI algorithms.
• Mentor or train teams and coordinate between research-oriented AI scientists and engineering teams to continuously improve models with production feedback.

Scaling & Performance

• Ensure AI solutions perform at scale, handling thousands of daily inferences with low latency and high reliability.
• Optimize model serving using techniques like model compression, caching, and hardware acceleration.

Implement robust monitoring and alerting for model performance to detect and address degradation (e.g., drift, latency issues).

Qualifications & Skills:

• 6+ years of experience
• Master’s or PhD in a relevant field (Computer Science, Software Engineering,  Machine Learning, Data Science, Statistics, etc.) is strongly preferred, especially with research or thesis work related to AI/ML
• LLM & GenAI Mastery: Expert in building and deploying LLM-based applications using RAG, prompt engineering, and vector databases. Skilled in LLMOps tools (LangChain, LlamaIndex) and fine-tuning models for enterprise use, including agent-based architectures.
• MLOps & Cloud Infrastructure: Proficient in cloud ML platforms (AWS, GCP, Azure) and MLOps workflows. Uses Docker, Kubernetes, and IaC tools (Terraform, CloudFormation) for scalable deployments. Experienced in CI/CD, real-time inference, GPU optimization, and ML observability (Prometheus, Grafana, MLflow).
• Full-Stack Development: Capable of building end-to-end AI solutions, from front-end (React) to back-end APIs (Flask, FastAPI, Node.js). Skilled in integrating ML models with databases (SQL, NoSQL) and delivering seamless user experiences through robust software engineering.
• Proficient in Python (pandas, scikit-learn), deep learning (PyTorch/TensorFlow/Keras), NLP/LLMs, LangChain, embeddings/vector search, and classic ML.
• Experienced with Snowflake-native ML (Snowpark Python, UDFs/UDTFs, Tasks/Streams).
• Competent in data engineering (SQL, ETL/pipelines, Spark/PySpark) and handling large structured/unstructured datasets.
• Strong understanding of AI/ML algorithms, application architecture, and design patterns.
• Excellent problem-solving, analytical, communication, and collaboration skills.

Preferred Qualifications & Skills

• Financial services domain experience (fraud risk, AML, underwriting, or commercial/treasury analytics).
• Hands-on experience with Snowflake ML/Snowpark (Python), Tasks/Streams, secure external functions, and feature management/registry tooling.
• Familiarity with fairness toolkits, XAI frameworks, and preparing models for validation, audit, or regulatory exams.
• Knowledge of SR 23‑4 (third‑party risk), NYC Local Law 144 (AEDT), NYDFS Part 500 (cyber).
• Ability to work in a constantly evolving environment.
• Excellent written and verbal communication skills.
• Strong listening and teaching abilities.
• Demonstrated analytical, troubleshooting, and problem-solving skills.
• Quick learner of new technologies.
• Self-directed with strong technology and communication skills.
• Ability to synthesize multiple sources of information and understand the broader operational context of the Bank.
• Collaborative team player with a practical and creative approach in a dynamic work environment.
• Ability to handle ambiguity, multitask, and adapt quickly to changing priorities.

Potential Salary: $130,000 - $200,000 annually

This salary range reflects base wages and does not include benefits, bonus, or incentive pay. Salary bands are purposefully wide ranging to encompass the different factors considered in determining where a candidate falls in the range, including but not limited to, seniority, performance, experience, education, and any other legitimate, non-discriminatory factor permitted by law. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed here.

Metropolitan Commercial Bank 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.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Come Work With Us:

Metropolitan Commercial Bank (“MCB” or the “Bank”) is a New York City–based, full-service commercial bank providing tailored banking solutions to businesses, institutions, and individuals. Founded in 1999, MCB operates banking centers in Manhattan and Boro Park, Brooklyn, within New York City, as well as in Great Neck on Long Island, New York, and Lakewood, New Jersey. The Bank recently expanded to Miami, Florida with their newest Brickell banking center.

Metropolitan Commercial Bank offers a comprehensive suite of commercial, business, and personal banking products and services to small businesses, middle-market and corporate enterprises, private and public institutions, municipalities, and local government entities.

The Bank has earned national recognition for its financial performance, innovation, and strategic growth. The Bank was named one of Newsweek’s Best Regional Banks in 2024 and 2025. Additionally, MCB recently received Editor’s Choice recognition at the Banking Tech Awards USA for Digital Onboarding & Omnichannel Banking and in 2026, the Bank earned Great Place To Work certification and received the Web Award Standard of Excellence for MCBankNY.com.

We are a client-focused organization that values technological innovation and excellence. A strong technical mindset, AI fluency, and adaptive skills are essential for our employees to effectively contribute to our mission and drive our success. We foster human–AI teaming and strong governance to ensure technology is used responsibly and in alignment with Bank policies and procedures. For more information about the Bank, please visit the Bank’s website at MCBankNY.com.

Position Summary:

Metropolitan Commercial Bank is seeking a VP-level Applied AI & Machine Learning Scientist to design, build, and validate production-grade AI/ML and Generative AI solutions in a highly regulated banking environment. This role focuses on high-impact use cases—fraud detection, AML alert optimization, AI-assisted credit memo generation for underwriting decision support, contact center AI assistant/copilots, and personalization for treasury/commercial clients—delivered with rigorous governance, explainability, fairness testing, privacy-by-design, cybersecurity, and model lifecycle controls aligned to SR 11-7 and MCB’s Trustworthy & Responsible AI Principles. The role emphasizes Snowflake as the primary ML platform (e.g., Snowpark Python, UDFs/UDTFs, Tasks/Streams, and Snowflake-native ML).

Standard 4-day in-office requirement, 1 day remote (of your choosing)

Essential Functions & Responsibilities 

Applied AI/ML development:

• Design and implement models for fraud detection, AML alert scoring/triage, AI-generated credit memo drafting and underwriting decision support, contact center AI assistants, and personalization for commercial/treasury use cases.
• Leverage modern methods: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings and vector databases, transformers, boosting, anomaly/outlier detection, and classical ML.
• Embed explainability (e.g., SHAP, interpretable scorecards/monotonic models) and conduct pre-/post-deployment bias testing with documented remediation.

Model validation, documentation & governance (SR 11‑7):

• Produce audit-ready documentation (methodology, assumptions, data lineage, limitations, testing) and register models in the inventory with owners/materiality.
• Facilitate independent validation/effective challenge; obtain required approvals before deployment; maintain change management and periodic review cadence.
• Define monitoring, drift thresholds, retraining triggers, and safe rollback/kill-switch procedures; maintain human-in-the-loop checkpoints for high-impact decisions.

Productionization & MLOps on Snowflake

• Package, deploy, and operate models via CI/CD, containerization, and model registry; instrument KPIs/KRIs and alerting dashboards. Operate models natively on Snowflake using Snowpark Python, UDFs/UDTFs, Tasks/Streams, and secure external access where required.
• Partner with Engineering to integrate models via secure APIs/batch; ensure scalability, resiliency, and observability in cloud/on‑prem (e.g., Snowflake, Azure ML, Databricks).

Regulatory, privacy, and cybersecurity alignment:

• Design for ECOA/Reg B (adverse action specificity), UDAAP, FCRA, GLBA privacy, and NYDFS 23 NYCRR 500 cybersecurity requirements.
• Apply privacy-by-design (data minimization, purpose limitation, retention), strong access controls/segregation, and secure SDLC/red teaming for GenAI stacks.

Third‑party AI & data stewardship:

• Support due diligence, testing, and ongoing monitoring of vendor AI/data providers per SR 23‑4; evaluate conceptual soundness, fairness, and security.
• Negotiate/verify contractual controls (no vendor training on MCB/NPI, subprocessors disclosure, audit rights, exit/portability).
• Ensure AEDT compliance (NYC Local Law 144) for any HR-related AI tools.

Cross‑functional partnership:

• Collaborate with Model Risk, Compliance/Legal, Cyber/IT, Data Privacy, Internal Audit, and business owners to meet objectives while staying within risk appetite.
• Communicate complex results, risks, and limitations clearly to technical and non‑technical stakeholders (management committees, examiners).

Innovation, coaching, and best practices:

• Evaluate emerging ML/GenAI methods, LLM evaluation techniques, Snowflake‑native capabilities (e.g., vector search, orchestration), and governance tooling; lead POCs within established control gates.
• Mentor junior staff; promote responsible AI practices, documentation standards, and reproducibility.

Qualifications & Skills:

• 6+ years of relevant work experience.
• Expertise in Python (pandas, scikit‑learn), deep learning (PyTorch/TensorFlow), NLP/LLMs, LangChain, embeddings/vector search, and classic ML.
• MLOps proficiency with CI/CD, containerization (Docker), registries, and observability; cloud ML (Snowflakes-native ML, Azure ML or Databricks preferred).
• Snowflake‑native ML proficiency: Snowpark Python, UDFs/UDTFs, Tasks/Streams; ability to build and operate ML workflows inside Snowflake.
• Data engineering competency (SQL, ETL/pipelines, Spark/PySpark); ability to work with structured/unstructured data.
• Explainability (e.g., SHAP) and fairness testing; ability to produce interpretable reason codes for ECOA/Reg B adverse actions as applicable.
• Strong grasp of SR 11‑7 lifecycle, model documentation, and operational monitoring within three lines of defense governance.
• Excellent communication; ability to translate technical detail to business/risk stakeholders and drive decisions.
• Curiosity and problem‑solving mindset; ability to balance innovation with disciplined risk management.

Preferred Qualifications & Skills

• Master’s or PhD in a relevant field (Computer Science, Machine Learning, Data Science, Statistics, etc.) is strongly preferred, especially with research or thesis work related to AI/ML, NLP, or model interpretability.
• Financial services domain experience (fraud risk, AML, underwriting, or commercial/treasury analytics).
• Hands-on with Snowflake ML/Snowpark (Python), Tasks/Streams, secure external functions; experience with feature management/registry tooling a plus. model registry and pipeline orchestration; Kubernetes a plus.
• RAG architectures, vector databases, prompt engineering, and LLM evaluation (accuracy, hallucination, safety).
• Fairness toolkits and XAI frameworks; experience preparing models for validation, audit, or regulatory exam discussions.
• Familiarity with SR 23‑4 (third‑party risk), NYC Local Law 144 (AEDT), NYDFS Part 500 (cyber).
• Ability to work in a constantly evolving environment
• Must have excellent written and verbal communication skills
• Must be a good listener and good teacher
• Demonstrate analytical, troubleshooting and problem-solving skills
• The ability to learn new technologies quickly
• Self-directed individual with technology and communication skills.
• Ability to take in multiple sources of information with an understanding of the bigger picture need, want, and operation of the Bank.
• Collaborative team-player who can find creative and practical solutions in a dynamic work environment.
• Ability to handle ambiguity, juggle multiple matters at once, and quickly and seamlessly shift from one situation or task to another.

Potential Salary: $130,000 - $200,000 annually

This salary range reflects base wages and does not include benefits, bonus, or incentive pay. Salary bands are purposefully wide ranging to encompass the different factors considered in determining where a candidate falls in the range, including but not limited to, seniority, performance, experience, education, and any other legitimate, non-discriminatory factor permitted by law. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed here.

Metropolitan Commercial Bank 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.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Scale AI’s Public Sector business is growing quickly as government agencies adopt AI to support critical national security, defense, and public sector missions. We are looking for a Mission Software Engineering Manager to join our dynamic Federal Engineering team. As a part of this team, you will play a critical role in supporting Scale’s government customers by scoping and developing onsite solutions. Our scalable, high-performance platform is the foundation for these customer solutions, and your expertise will be instrumental in designing and implementing systems that can handle interactions with existing customer systems to help our products integrate into existing customer workflows.  

You will:

• Recruit a high-performing engineering team. 
• Drive engineering productivity. Provide guidance, mentorship, and technical leadership to a team of engineers working on Generative AI projects. 
• Collaborating with cross-functional teams to define, design, and execute strategic roadmap.
• Work directly with customers to understand their problems and translate those into features in Scale’s platform.
• Be open to ~25% travel or relocation to a key customer geographic location.
• Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back.
• Deploy and maintain Scale software at customer sites
• Develop customer requested features and work closely with them to ensure that they win customer love.
• Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• This role will require an active TS/SCI security clearance or the ability to obtain a security clearance.

Ideally you’d have:

• 5+ years of full-time engineering experience, post-graduation
• 2+ years of prior engineering management or equivalent experience and has managed an engineering team.
• Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles.

• Prior experience developing with Python and JavaScript, or other modern software languages. Familiarity with Node and React is a plus.
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
• Linux experience: Understanding of shell scripting, operating systems, etc
• Networking experience: Understanding of networking technologies, configuration  (ports, protocols, etc) 
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles
• Understand unique DoD and USG constraints when it comes to technology

As a Software Engineer on the Machine Learning Infrastructure team, you will build the "Operating System" for our large-scale GPU clusters. You will architect a high-performance training platform that handles the immense complexity of multi-thousand GPU workloads, ensuring every cycle is used efficiently. Your work directly determines the velocity at which our researchers can train and iterate on the world’s most advanced models.

The ideal candidate is a systems expert who thrives on solving the orchestration, networking, and reliability challenges that emerge at massive scale. You will partner closely with researchers to build a seamless, resilient environment that transforms raw compute into breakthrough AI.

You will:

• Architect and scale a multi-tenant orchestration layer that abstracts away the complexity of GPU clusters, ensuring high utilization and seamless job recovery.
• Design and implement scheduling primitives to optimize the lifecycle of training jobs.
• Develop deep observability and automated health-checking into the training stack to proactively identify and isolate hardware failures
• Evaluate and integrate emerging technologies in the CNCF and AI ecosystem (e.g. Ray, Kueue), making data-driven build vs. buy decisions that balance velocity with long-term maintainability.
• Work closely with Finance and Procurement teams to drive our capacity planning process.
• Participate in our team’s on call process to ensure the availability of our services.
• Own projects end-to-end, from requirements, scoping, design, to implementation, in a highly collaborative and cross-functional environment.

Ideally you'd have:

• 5+ years of experience in backend or infrastructure engineering, with at least 2 years focused on orchestrating ML workloads at scale (100+ GPU nodes).
• Strong programming skills in one or more languages (e.g. Python, Go, Rust, C++)
• Experience with complex compute management systems that cover queueing, quotas, preemption, and gang scheduling.
• Experience with distributed training infrastructure, such as EFA, Infiniband, and topology-aware scheduling.
• Experience with distributed storage systems (e.g. Lustre, S3) as they relate to training throughput
• Expert-level knowledge of Kubernetes internals (Custom Resources, Operators, Admission Controllers) and how they interact with device plugins for specialized hardware.
• Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
• Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to haves:

• Experience with distributed training techniques such as DeepSpeed, FSDP, etc.
• Experience with the NVIDIA software and hardware stack (CUDA, NCCL)
• Experience with PyTorch
• Familiarity with post-training algorithms such as GRPO, and with Reinforcement Learning

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability.

You will:

• Own large new areas within our product
• Work across backend, frontend, and interacting with LLMs and ML models
• Deliver experiments at a high velocity and level of quality to engage our customers
• Work across the entire product lifecycle from conceptualization through production
• Be able, and willing, to multi-task and learn new technologies quickly

Ideally you'd have:

• 4+ years of full-time engineering experience, post-graduation
• Experience scaling products at hyper growth startups
• Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies
• Proficient in Python or Javascript/Typescript, and SQL
• Experience with Kubernetes
• Experience with major cloud providers (AWS, Azure, GCP)

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition.

At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.

At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems.  You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.

You will:

• Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements.
• Collaborate with cross-functional teams to define, design, and deliver new features.
• Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades.
• Present technical information to teams and stakeholders, providing guidance and insight on development processes and technologies.
• Provide technical leadership, including: upholding and upleveling engineering standards across the organization, mentoring junior engineers. 

Ideally you’d have:

• 8+ years of full-time engineering experience, post-graduation with specialties in back-end systems, specifically related to building large-scale data storage, streaming, and warehousing systems.
• Extensive experience in various database technologies (MongoDB, Postgres), streaming/processing solutions (Kinesis, Flink, Spark), indexing/caching (ElasticSearch, Redis), and various data query engines (Trino, Presto, Snowflake, etc.).
• Show a track record of mentoring and leading teams in successful projects.
• Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders.
• Experience working fluently with standard containerization & deployment technologies like Kubernetes and various public cloud offerings.
• Extensive experience in software development and a deep understanding of distributed systems, cloud platforms and data systems.
• Experience driving cross functional collaboration and communication at an organizational or broader level. 

Nice to haves:

• Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI).
• Experience with performance tuning and cost optimizations of cloud based data platforms. 
• Experience defining a data lifecycle strategy and designing/implementing tooling for data privacy (i.e. GDPR) needs.  
• Experience scaling products at hyper-growth startups.
• Excitement to work with AI technologies.

About Scale AI

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.

Role Overview

As a Forward Deployed AI Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments.

This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Key Responsibilities

Customer Integration & Deployment

• Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements
• Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
• Deploy and configure AI models and agents within customer security and compliance boundaries

AI Agent Development

• Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
• Architect multi-agent systems that orchestrate between different models, tools, and data sources
• Implement evaluation frameworks to measure agent performance and iterate toward business objectives
• Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement

Prompt Engineering & Optimization

• Create sophisticated prompt engineering strategies optimized for customer-specific domains and data
• Build and maintain prompt libraries, templates, and best practices for customer use cases
• Conduct systematic prompt experimentation and A/B testing to improve model outputs
• Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate

Technical Leadership & Collaboration

• Serve as the primary technical point of contact for strategic enterprise accounts
• Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration
• Provide technical training and knowledge transfer to customer teams
• Work closely with Scale's product and engineering teams to translate customer needs into product improvements
• Document technical architectures, integration patterns, and best practices

Problem Solving & Innovation

• Debug complex technical issues across the entire stack, from data pipelines to model outputs
• Rapidly prototype solutions to unblock customers and prove out new use cases
• Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems
• Identify opportunities for productization based on common customer patterns

Required Qualifications

• 4+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design
• Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
• Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure
• Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences

Preferred Qualifications

Agent Development Wiz

• Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
• Experience building and deploying AI agents or autonomous systems in production
• Knowledge of vector databases and semantic search systems
• Contributions to open-source AI/ML projects

Infrastructure Guru

• Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
• Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
• Previous work in a devops, platform, or infra role
• Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)

Customer Product Whisperer

• Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
• Domain expertise in verticals like finance, healthcare, government, or manufacturing
• Experience with technical enablement or teaching programs

Sample Projects

The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, integrate directly into customers’ existing systems, and are deployed on their infrastructure.

Deep Research for Due Diligence

For a global professional services firm, we developed a sophisticated deep research agent to assist in due diligence. This agent employs a multi-agent architecture for robust fact-checking, integrates several internal MCP tools, and processes complex, unstructured data sources. This solution reliably saves employees hundreds of hours weekly.

Churn Prediction

Working with a TelCo organization, we built a model utilizing customer data to predict churn likelihood. The system then curates personalized offers based on this prediction. This model was integrated into a "next best action" copilot, enabling call center agents to proactively surface relevant offers to customers, leading to a significant reduction in churn.

Data Extraction Voice Agent

We partnered with a healthcare organization to create a lifelike voice agent and avatar designed to gather unstructured health information from patients. Engineered for low latency, the agent adeptly manages conversational flow, adheres to safety guardrails, and efficiently handles data extraction. This automation saves the organization's nurses hundreds of hours each week.

Scale is a vital part of bringing AI-enabled technologies to the world, from autonomous driving to drones, robots, and large language models. For example, Scale works with the world's top self-driving car and robotics ML teams as well as the largest companies in the generative AI space. 

As our customer base is growing, you will be on the front lines of our field engineering efforts for our federal AI projects, having the opportunity to meaningfully impact millions of dollars in revenue by working closely with our largest public sector customers and ensuring that they become passionate, lifelong Scale customers.

Our Field Engineers ensure customers' experiences with Scale's technology are seamless and optimized to build a successful, long-term partnership. Field Engineers partner closely with Product, Engineering, and Operations to lead existing customers through building production-grade data pipelines. We do this by knowing our customer’s use-cases inside and out, and creating the tooling and documentation needed to scalably support their growth.

Field Engineers in general are experts on Scale's products and codebase, and have general technical knowledge on web development, using APIs, and working with large volumes of data. Field Engineers are strong relationship builders, great project managers, and always fun to work with. 

The ideal person is a software engineer generalist who enjoys working with clients directly, taking ambiguous requirements and issues, and quickly designing and building sustainable solutions in close collaboration with the Product and Engineering teams. This role is at the intersection of customer delivery, product, and engineering, giving you a breadth of experience and fully leveraging both sides of your brain. If this sounds like you, we invite you to apply!

You will:

• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back
• Work closely with our customer’s engineering teams to optimize data pipelines, including providing input towards designing API endpoints and input/output schemas
• Design, develop and maintain playbooks, internal tools, Scale’s documentation and SDKs to quickly get customers set up for long-term success
• Partner with Software Engineers and Operations to remove any technical hurdles customers may face / Debug technical issues impacting delivery and own technical escalations coming from the customer
• Be accountable for the customer’s technical experience throughout their time with Scale
• Work with AEs and PMs to identify customer-specific feature requests
• Develop technical domain expertise in areas of Large Language Models, 2D Image Annotation, and working with API integrations
• Evangelize Scale and interact with customers at major events
• Have an active TS/SCI clearance

Ideally you'd have:

• Track record of success as a hybrid customer-facing engineer or similar function, wearing multiple hats along the way
• Prior technical hands-on experience working with clients in a pre or post-sales capacity to realize business goals
• Prior experience developing with Python and JavaScript, or other modern software languages
• Strong engineering background preferably in Computer Science, Mathematics, or other quantitative fields
• Strong project management and interpersonal skills
• Presentation skills with a high degree of technical credibility when speaking with executives and front-line engineers
• High level of comfort communicating effectively across internal and external organizations
• Intellectual curiosity, empathy, and ability to operate with high velocity

Nice to haves:

• Experience in AI
• Experience working in classified environments
• Previous experience as a technical go-to-market resource
• Understanding of DevSecOps principles, including secure software delivery, infrastructure as code, and continuous integration/deployment
• Hands-on knowledge of container orchestration with Kubernetes and experience with Helm charts for application deployment
• Experience automating infrastructure and configuration management using Ansible or similar tools

Scale AI is seeking a highly skilled and motivated Software Engineer, ARC (Architecture, Reliability, & Compute) to join our dynamic Public Sector Engineering team. As a part of this team, you will define how the company ships software, establishing the patterns for deploying into complex government and high-security environments, rather than just running Terraform scripts. You will build and maintain internal CLIs/tools that standardize testing, deployment, environment management and are tools that engineering relies on to prevent downstream breakages. You will execute on automated deployment efforts to pay down tech debt, creating fully functional staging/testing environments, and defining the company's standard for safe deployments.

You will:

• Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure.
• Own services or systems and define their long-term health goals, while also improving the health of surrounding components.
• Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product.
• Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings.

Must have:

• At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance

Ideally you'd have:

• Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web development frameworks, programming languages, and databases. Experience with developing & delivering software to air-gapped & isolated environments is a plus.
• Cloud-Native Technologies: Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is desired. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. 
• Security Focused: Experience with Federal Compliance frameworks, and requirements(e.g, Cloud SRG, FedRAMP, STIG Benchmarks, etc). Experience developing software & technical solutions that meet strict security & regulatory compliance requirements.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles.
• Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment.
• Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering.
• Must be able to support work 3-4 days a week from the DC, SF, NYC, or STL office.

Scale AI is seeking a highly skilled and motivated Software Engineer, Frontier AI Infrastructure to join our dynamic Public Sector Engineering team. As a part of this team, you will own the model inference layer - enabling state of the art models, debugging the latest AI tools, managing networking, debugging latency, and tracking pricing/usage metrics for AI models. You will lead technical discussions on the frontlines with cloud vendors and customers to deliver on critical contracts and to debug platform issues. You will also work upstream with Product to understand features before they break, moving us from "infra-only debugging" to proactive integration testing.

You will:

• Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure.
• Own services or systems and define their long-term health goals, while also improving the health of surrounding components
• Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product.
• You will work with Product to build integration tests that catch issues early, shifting the focus from "infra-only debugging" to preventing failures upstream.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings.

Must have:

• At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance

Ideally you'd have: 

• Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web development frameworks, programming languages, and databases. Experience with developing & delivering software to air-gapped & isolated environments is a plus.
• Cloud-Native Technologies: Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is desired. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. 
• Security Focused: Experience with Federal Compliance frameworks, and requirements(e.g, Cloud SRG, FedRAMP, STIG Benchmarks, etc). Experience developing software & technical solutions that meet strict security & regulatory compliance requirements.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles.
• Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment.
• Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering.
• Must be able to support work 3-4 days a week from the DC, SF, NYC, or STL office.

About Scale AI

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.

Role Overview

As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments.

This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Key Responsibilities

Customer Integration & Deployment

• Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements
• Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
• Deploy and configure AI models and agents within customer security and compliance boundaries

AI Agent Development

• Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
• Architect multi-agent systems that orchestrate between different models, tools, and data sources
• Implement evaluation frameworks to measure agent performance and iterate toward business objectives
• Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement

Prompt Engineering & Optimization

• Create sophisticated prompt engineering strategies optimized for customer-specific domains and data
• Build and maintain prompt libraries, templates, and best practices for customer use cases
• Conduct systematic prompt experimentation and A/B testing to improve model outputs
• Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate

Leadership & Collaboration

• Serve as the Engineering Manager and technical point of contact for strategic enterprise accounts
• Lead a team that is collaborating with customer data scientists, ML engineers, and software developers to ensure smooth integration
• Work closely with Scale's product and engineering teams to translate customer needs into product improvements
• Document technical architectures, integration patterns, and best practices

Problem Solving & Innovation

• Debug complex technical issues across the entire stack, from data pipelines to model outputs
• Rapidly prototype solutions to unblock customers and prove out new use cases
• Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems
• Identify opportunities for productization based on common customer patterns

Required Qualifications

• 5+ years of software engineering experience with 2+ yrs of  Management experience with strong fundamentals in data structures, algorithms, and system design
• Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
• Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure
• Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences

Preferred Qualifications

Agent Development Wiz

• Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
• Experience building and deploying AI agents or autonomous systems in production
• Knowledge of vector databases and semantic search systems
• Contributions to open-source AI/ML projects

Infrastructure Guru

• Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
• Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
• Previous work in a devops, platform, or infra role
• Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)

Customer Product Whisperer

• Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
• Domain expertise in verticals like finance, healthcare, government, or manufacturing
• Experience with technical enablement or teaching programs

Sample Projects

The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, integrate directly into customers’ existing systems, and are deployed on their infrastructure.

Deep Research for Due Diligence

For a global professional services firm, we developed a sophisticated deep research agent to assist in due diligence. This agent employs a multi-agent architecture for robust fact-checking, integrates several internal MCP tools, and processes complex, unstructured data sources. This solution reliably saves employees hundreds of hours weekly.

Churn Prediction

Working with a TelCo organization, we built a model utilizing customer data to predict churn likelihood. The system then curates personalized offers based on this prediction. This model was integrated into a "next best action" copilot, enabling call center agents to proactively surface relevant offers to customers, leading to a significant reduction in churn.

Data Extraction Voice Agent

We partnered with a healthcare organization to create a lifelike voice agent and avatar designed to gather unstructured health information from patients. Engineered for low latency, the agent adeptly manages conversational flow, adheres to safety guardrails, and efficiently handles data extraction. This automation saves the organization's nurses hundreds of hours each week.

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes:

• Create multi-layered guardrails around agents
• Optimize data retrieval for agents
• Orchestrate fleets of asynchronous agents
• Automatically alerts users to deviations in data
• Illustrating how an agent reached a decision

As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders.

You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers.

• Manage the full lifecycle of feature development from requirement definition to deployment on classified networks.
• Direct the orchestration of asynchronous agent fleets to meet mission requirements.
• Lead customer engagements to translate mission needs into technical requirements.
• Own the communication with stakeholders to ensure implementation meets defined acceptance criteria.
• Conduct technical reviews and identify risks within machine learning infrastructure and model serving.
• Drive the platform roadmap by providing technical specifications for Federal product offerings.

Ideally you will have: 

• Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
• AI Application Integration: Familiarity with integrating Large Language Models (LLMs) and building agentic workflows. Understanding of prompt engineering, retrieval-augmented generation (RAG), and agent orchestration is beneficial.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles
• Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment
• Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to defining and evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering

Senior Software Engineer, Platform — Connectivity

The Connectivity team owns the core platform that enables Scale to continuously generate, evaluate, and deliver high-quality training data to our customers. Our systems sit at the center of Scale’s data and AI infrastructure, powering large-scale workflows while supporting frontier AI capabilities such as multi-modality, long-horizon reasoning, and agentic behavior.

We’re looking for a senior engineer with deep experience building robust platforms, someone who brings strong architectural judgment, a bias toward correctness and reliability, and the ability to design systems that scale and evolve cleanly over time. This is a backend-heavy role with full-stack expectations and significant ownership from design through long-term operation.

What You’ll Do

• Design and own foundational platform systems that support scalable data generation, evaluation, and bespoke customer delivery across Scale’s ecosystem.
• Architect extensible, production-grade services that can support frontier AI workflows, including multi-modal inputs, long-running processes, and agentic orchestration.
• Build and operate distributed systems at scale, with strong guarantees around correctness, reliability, observability, and cost efficiency.
• Integrate with public LLM APIs and AI services, designing abstractions that are resilient to model churn, latency variability, and evolving usage patterns.
• Design and maintain data transformation and processing systems, supporting complex schema evolution, customization, and high-throughput workloads.
• Partner closely with infrastructure, product, and customer-facing teams to define requirements, shape technical direction, and deliver seamless integration experiences for customers.
• Lead multi-quarter technical initiatives, including authoring and driving a 6+ month technical roadmap for major platform investments.
• Apply strong engineering judgment in ambiguous problem spaces, balancing speed with long-term maintainability and operational excellence.
• Raise the quality bar through thoughtful system design reviews, rigorous code reviews, and mentorship grounded in real-world production experience.

Ideal Experience

• 7+ years of professional software engineering experience, with a strong background in building and operating large-scale, production-grade platforms.
  
  
• Deep expertise in distributed systems and cloud-native architectures, including Kubernetes, microservices, event-driven systems, caching, and production databases.
  
  
• Proven ability to lead multi-quarter technical initiatives, work effectively across cross-functional teams, and apply strong architectural judgment in ambiguous environments.
  
  
• Preferred: Experience integrating with public LLM APIs and designing systems that handle scale, reliability, latency, and cost tradeoffs.
  
  

Preferred: Experience building or operating data processing and transformation systems supporting complex workflows and evolving schemas.

Scale AI is seeking a highly skilled and motivated Mission Software Engineer to join our dynamic Federal Engineering team. As a part of this team, you will play a critical role in supporting Scale’s government customers by scoping and developing onsite solutions. Our scalable, high-performance platform is the foundation for these customer solutions, and your expertise will be instrumental in designing and implementing systems that can handle interactions with existing customer systems to help our products integrate into existing customer workflows.   

You will:

• Work directly with customers to understand their problems and translate those into features in Scale’s platform.
• Be open to >50% travel or relocation to a key customer geographic location.
• Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back
• Deploy and maintain Scale software at customer sites
• Develop customer requested features and work closely with them to ensure that they win customer love.
• Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• This role will require an active TS/SCI security clearance or the ability to obtain a security clearance.

Ideally you have:

• Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles.
• Prior experience developing with Python and JavaScript, or other modern software languages. Familiarity with Node and React is a plus.
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
• Linux experience: Understanding of shell scripting, operating systems, etc
• Networking experience: Understanding of networking technologies, configuration  (ports, protocols, etc) 
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles

Scale AI’s Public Sector business is growing quickly as government agencies adopt AI to support critical national security, defense, and public sector missions. We’re looking for a hands-on Field Engineering Manager on the front lines leading a team of our field engineering efforts for our federal AI projects, having the opportunity to meaningfully impact millions of dollars in revenue by working closely with our largest public sector customers and ensuring that they become passionate, lifelong Scale customers. This role is ideal for someone who thrives in technical environments, enjoys managing teams while staying close to the code, and wants to work on meaningful problems that impact real world operations across the U.S. government. 

Field Engineers are software engineering generalists who enjoy working with clients directly, taking ambiguous requirements and issues, and quickly designing and building production-grade solutions in close collaboration with the Product, Engineering, and Delivery teams. Field Engineers are experts on Scale's products and codebase, and have general technical knowledge on GenAI systems, APIs, networking, and data engineering. Field Engineers are strong relationship builders, great project managers, and always fun to work with. You’ll play a critical role in delivering technical solutions—all while helping your team grow and execute.

You’ll split your time between technical planning and execution (50%) and people management and team development (50%), leading a team of 6-8 engineers. You’ll work cross-functionally with product, engineering, security, and delivery teams to ensure our engineering efforts meet complex federal compliance, security, and performance needs.

Day to day:

• 50% Field engineering - customer engagement, technical development and delivery 
• 50% Managing a growing team

You will:

• Recruit a high-performing engineering team. 
• Drive engineering productivity. Provide guidance, mentorship, and technical leadership to a team of customer facing engineers working on Generative AI projects. 
• Collaborating with cross-functional teams to define, design, and execute strategic roadmap based on customer needs.
• Work directly with customers to understand their problems and translate those into custom workflows within Scale’s platform.
• Be open to ~25% travel or relocation to a key customer geographic location.
• Collaborate with cross-functional teams to define the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• Lead end-to-end technical delivery of custom workflows from scoping to development to testing to implementation
• This role will require an active TS/SCI security clearance or the ability to obtain a security clearance.

Ideally you’d have:

• 5+ years of full-time engineering experience, post-graduation.
• 2+ years of prior engineering management or equivalent experience and previously managed an engineering team.
• Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles.
• Prior experience developing with Python and JavaScript, or other modern software languages. 
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus.
• Linux experience: Understanding of shell scripting, operating systems, etc.
• Networking experience: Understanding of networking technologies, configuration  (ports, protocols, etc) is a plus.
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles.
• Understand unique DoD and USG constraints when it comes to technology.

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are seeking a strong Senior Full-Stack Engineer to help us build, scale, and refine our rapidly growing product. The ideal candidate is deeply grounded in software engineering best practices and experienced in developing and scaling modern web applications end-to-end. You will work across the stack—from React/TypeScript frontends to Python-based backends—while integrating with LLMs and machine learning systems.

You will solve complex challenges in scalability, reliability, and product experience while owning significant product areas in a fast-paced environment.

What You’ll Do

• Own major full-stack product areas, driving features from design through production deployment.
  
  
• Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness.
  
  
• Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components.
  
  
• Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences.
  
  
• Deliver experiments and new features quickly, maintaining high quality and tight feedback loops with customers.
  
  
• Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP.
  
  
• Adapt quickly—learning new technologies, frameworks, and tools as needed across the stack.
  
  

Ideal Experience

• 5+ years of full-time engineering experience, post-graduation.
  
  
• Strong experience developing full-stack applications using React, TypeScript, and Python.
  
  
• Experience scaling or shipping products at high-growth startups.
  
  
• Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome).
  
  
• Proficiency with SQL and modern API development.
  
  
• Experience with Kubernetes, containerization, and microservice architectures.
  
  
• Experience working with at least one major cloud provider (AWS, GCP, or Azure).

We are seeking a highly technical Security Engineer to join our Product Security team. This role is integral to ensuring the security and integrity of our products and services. You will conduct in-depth code reviews, implement security best practices, and influence the overall security strategy. Your expertise in TypeScript, Python, AWS, CI/CD, SAST, DAST, and terraform orchestration will be crucial in identifying and mitigating potential security vulnerabilities. You will also structure complex problems, diagnose root causes independently, and clearly explain the mechanics and significance of security vulnerabilities, including their exploitability and potential impact.

You will:

• Leverage broad product security expertise to build and maintain software tooling that secures every layer of the modern AI/ML software ecosystem.
• Conduct in-depth code reviews to identify and remediate security vulnerabilities.
• Evaluate and enhance the security of our product offerings, through RFC and service review.
• Implement and maintain CI/CD pipelines with a strong focus on security.
• Perform Static Application Security Testing (SAST) and Dynamic Application Security Testing (DAST) to identify vulnerabilities in production code.
• Utilize terraform orchestration to ensure secure and efficient infrastructure management.
• Guide engineering teams to build robust long-term solutions that consider security and privacy. 
• Clearly explain the mechanics and significance of security vulnerabilities, including their exploitability and potential impact.
• Influence the security strategy and direction of the team, advocating for best practices and continuous improvement.

Ideally, you’d have:

• Demonstrated ability to drive multi-month security initiatives independently, from problem definition through execution, without requiring significant direction.
• Proven experience as a Security Engineer with a focus on product security.
• Proficiency in NodeJS, TypeScript, Python, and/or Kubernetes.
• Strong understanding of modern Javascript application design.
• Production experience operating and securing AWS infrastructure at scale.
• Hands-on experience with SAST and DAST tools and methodologies.
• Familiarity with terraform orchestration for infrastructure management.
• You can structure complex problems and diagnose root causes independently, providing actionable insights without requiring manager input.
• Excellent communication skills, with the ability to clearly present technical concepts and their implications to both technical and non-technical stakeholders.
• Demonstrated ability to influence security strategies and drive improvements within a team.
• Relevant security certifications (e.g., CISSP, CEH, OSCP) are a plus.

As a Software Engineer on the ML Infrastructure team, you will design and build platforms for scalable, reliable, and efficient serving of LLMs. Our platform powers cutting-edge research and production systems, supporting both internal and external use cases across various environments.

The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging research and engineering to deliver seamless experiences to our customers and accelerate innovation across the company.

You will:

• Build and maintain fault-tolerant, high-performance systems for serving LLMs workloads at scale.
• Build an internal platform to empower LLM capability discovery.
• Collaborate with researchers and engineers to integrate and optimize models for production and research use cases.
• Conduct architecture and design reviews to uphold best practices in system design and scalability.
• Develop monitoring and observability solutions to ensure system health and performance.
• Lead projects end-to-end, from requirements gathering to implementation, in a cross-functional environment. 

Ideally you'd have:

• 5+ years of experience building large-scale, high-performance backend systems.
• Strong programming skills in one or more languages (e.g., Python, Go, Rust, C++).
• Experience with LLM serving and routing fundamentals (e.g. rate limiting, token streaming, load balancing, budgets, etc.)
• Experience with LLM capabilities and concepts such as reasoning, tool calling, prompt templates, etc.
• Experience with containers and orchestration tools (e.g., Docker, Kubernetes).
• Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
• Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to haves:

• Experience with modern LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or text-generation-inference.

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability.

You will:

• Own large new areas within our product
• Work across backend, frontend, and interacting with LLMs and ML models
• Deliver experiments at a high velocity and level of quality to engage our customers
• Work across the entire product lifecycle from conceptualization through production
• Be able, and willing, to multi-task and learn new technologies quickly

Ideally you'd have:

• 7+ years of full-time engineering experience, post-graduation
• Experience scaling products at hyper growth startups
• Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies
• Proficient in Python or Javascript/Typescript, and SQL
• Experience with Kubernetes
• Experience with major cloud providers (AWS, Azure, GCP)

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes:

• Create multi-layered guardrails around agents
• Optimize data retrieval for agents
• Orchestrate fleets of asynchronous agents
• Automatically alerts users to deviations in data
• Illustrating how an agent reached a decision

As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders.

You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency.

• Define technical strategy for agentic guardrails, explainability, and fleet orchestration.
• Ensure system reliability and performance across multiple security classifications and network types.
• Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance.
• Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members.
• Influence the long-term product strategy and technical roadmap for the Federal business unit.
• Consult on the architecture of AI-powered solutions for large-scale federal contracts.

Ideally you will have: 

• Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
• AI Application Integration: Familiarity with integrating Large Language Models (LLMs) and building agentic workflows. Understanding of prompt engineering, retrieval-augmented generation (RAG), and agent orchestration is beneficial.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles
• Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment
• Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to defining and evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. 

The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail.

What You’ll Do:

• Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers
• Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs.
• Deliver experiments at a high velocity and level of quality to engage our customers
• Work across the entire product lifecycle from conceptualization through production
• Be able, and willing, to multi-task and learn new technologies quickly

What We’re Looking For:

• 4+ years of full-time engineering experience, post-graduation
• Experience scaling products at hyper growth startups
• Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies
• Proficient in Python or Javascript/Typescript, and SQL
• Experience with Kubernetes
• Experience with major cloud providers (AWS, Azure, GCP)
• Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences

Scale AI is at the forefront of the AI revolution, helping the U.S. government unlock the potential of AI across national security missions. We’re building enterprise-grade generative AI solutions and delivering them into operational use cases that matter.

The Global Forward Deployments (GFD) organization operates as a critical horizontal layer across Scale, sitting at the intersection of Engineering, Product, Design (EPD), Delivery, and GTM. As our business scales, we are growing the GFD Project Management Office (PMO) to act as the connective tissue that brings structure to ambiguity by aligning teams, organizing cross-functional workstreams, and keeping priorities coordinated across the organization.

As a Technical Program Manager within this expanding PMO, you will drive execution across diverse initiatives by partnering closely with Infrastructure & Security, Product, Software Engineering, Machine Learning, Mission/Field Engineering, Delivery, and Go-To-Market (GTM) teams. Your focus will be integrating engineering roadmaps, customer delivery timelines, and security constraints to enable successful deployments in complex, isolated environments.

What You Will Do

• Lead as a Horizontal PMO Partner: Serve as a central node within the growing GFD PMO, driving alignment across Engineering, Product, and Design (EPD) initiatives and ensuring priorities remain top-of-mind across the organization.
• Spearhead Niche Initiatives: Take on Scale’s difficult-but-ambiguous problems, breaking them down in a structured way and driving them to successful outcomes. You will dive into both technology and organizational processes to craft effective solutions and gain efficiencies, track resourcing and vendor management, and align internal resources to solve unique organizational, and technical challenges. 
• Bridge EPD, Delivery, and GTM: Act as the primary technical program manager uniting GFD with Product, ML, Mission & Field Engineering, Delivery, and GTM teams to wrangle contractual deliverables across EPD, unblock complex custom integrations, and drive technical milestones against critical contract checkpoints.
• Optimize Cross-Functional Processes: Collaborate with stakeholders across the company to improve processes and procedures, ensuring Scale's continued success.
• Foster Communication: Create an effective feedback loop between all teams within EPD as well as with partner teams like Legal, BizOps, and Partnerships.
• Navigate Ambiguity: Transition AI/ML technologies and processes into working Public Sector products/solutions even when requirements are undefined or ambiguous.

Ideally You’d Have

• Current or past Security Clearance (TS/SCI preferred).
• Proven experience partnering closely with Product and cross-functional Engineering teams to align technical roadmaps, manage dependencies, and drive complex, multi-team initiatives.
• Experience in project management, including planning, organizing, and managing resources.
• A demonstrated capacity to operate effectively and maintain high-quality output within a high-tempo, ambiguous, or chaotic environment.
• Experience in security and compliance, with a focus on cross-departmental collaboration.
• Experience in delivering secure and reliable solutions within classified, isolated, and air-gapped environments.
• Demonstrated understanding of security practices within cloud environments (e.g., AWS, Azure, GCP).
• Experience in a high growth, fast-paced technology company.
• An action-oriented mindset, balancing creative problem-solving with a strong drive to achieve outcomes.

Nice to Haves

• Experience in microservice design and Kubernetes-based container orchestration.
• Experience applying AI or Machine Learning.
• Strong analytical skills, with experience using data analysis tools or software.
• Demonstrated history of fostering cross-functional collaboration with Delivery, Sales, and Engineering teams.
• Backlog refinement & roadmapping experience with tools like Linear and JIRA.
• Proven experience translating complex SOW requirements into tactical engineering deliverables 
• Experience maintaining alignment with organizational capacity planning and delivery timelines.
• Background in Software, Security, or System Engineering.

(Note this role must be based within the continental United States and requires current US Citizenship to support Scale’s Public Sector business.)

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition.

At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.

At the foundation of these products is the Platform Engineering team. As a Staff Software Engineer, you will define and drive both the architectural roadmap and implementation of core platforms and software systems. You will be responsible for providing high-level vision and driving adoption across the engineering org for orchestration, data abstraction, data pipelines, identity & access management, and underlying cloud infrastructure.  You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.

Impact and Responsibilities:

• Architectural Vision: You will drive the design and implementation of foundational systems, acting as a bridge between high-level business goals and technical goals.
• Cross-Functional Leadership: You will collaborate with cross-functional teams to define and drive adoption of the next generation of features for our AI data infrastructure.
• Technical Ownership: You are responsible for proactively identifying and driving opportunities for organizational growth, driving improvements in programming practices, and upgrading the tools that define our development lifecycle.
• Technical Mentorship: You will serve as a subject matter expert, presenting technical information to stakeholders and providing the guidance to elevate the engineering culture across the company.

Ideally you’d have:

• 8+ years of full-time engineering experience, post-graduation with specialities in back-end systems.
• Extensive experience in software development and a deep understanding of distributed systems and public cloud platforms (AWS preferred).
• Demonstrated a track record of independent ownership and leadership across successful multi-team engineering projects
• Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders.
• Experience working fluently with standard containerization & deployment technologies like Kubernetes, Terraform, Docker, etc.
• Experience with orchestration platforms, such as Temporal and AWS Step Functions.
• Experience with NoSQL document databases (MongoDB) and structured databases (Postgres).
• Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI, ArgoCD).

Nice to haves:

• Experience with data warehouses (Snowflake, Firebolt) and data pipeline/ETL tools (Dagster, dbt).
• Experience scaling products at hyper-growth startups.
• Excitement to work with AI technologies.

About the Role

Anthropic manages one of the largest and fastest-growing accelerator fleets in the industry — spanning multiple accelerator families and clouds. The Accelerator Capacity Engineering (ACE) team is responsible for making sure every chip in that fleet is accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute.

As an engineer on ACE, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend.

You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment.

What This Team Owns

The team’s work spans three functional areas. Depending on your background and interests, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap:

• Data infrastructure — collecting, normalizing, and serving the fleet-wide data that powers everything else. This means building pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalizing billing and usage data across cloud providers, and maintaining the BigQuery layer that the rest of the org queries against. Correctness, completeness, and latency matter here.

• Fleet observability — making the state of the accelerator fleet legible and actionable in real time. This means building cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and driving systemic improvements to scheduling and fragmentation. The work sits at the intersection of Kubernetes operations and cross-team coordination.

• Compute efficiency — measuring and improving how effectively every major workload uses the hardware it’s running on. This means instrumenting utilization metrics across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and collaborating directly with system-owning teams to close efficiency gaps.

• Internal compute tooling — building the platforms and interfaces that make capacity data usable across the org. This includes capacity planning tools, workload attribution systems, cost dashboards, and self-service APIs. The consumers are research engineers, infrastructure teams, finance, and leadership — each with different needs and different levels of technical depth. The work involves product thinking as much as engineering: figuring out what people actually need, defining schema contracts, and making the data discoverable.

You will be placed on a pod based on your background and interests. We are especially focused on hiring for Data Platform, but strong candidates for any of the three active pods will move forward.

What You’ll Do

• Build and operate data pipelines that ingest accelerator occupancy, utilization, and cost data from multiple cloud providers into BigQuery. Own data completeness, latency SLOs, gap detection, and backfill automation.

• Develop and maintain observability infrastructure — Prometheus recording rules, Grafana dashboards, and alerting systems — that surface actionable signals about fleet health, occupancy, and efficiency.

• Instrument and analyze compute efficiency metrics across training, inference, and eval workloads. Build benchmarking infrastructure, establish per-config baselines, and work with system-owning teams to improve utilization.

• Build internal tooling and platforms that enable capacity planning, workload attribution, and cluster debugging. The consumers are other engineering teams, finance, and leadership — not external users.

• Operate Kubernetes-native systems at scale — deploying data collection agents, managing workload labeling infrastructure, and understanding how taints, reservations, and scheduling affect capacity.

• Normalize and reconcile data across heterogeneous sources — including AWS, GCP, and Azure billing exports, vendor-specific telemetry formats, and internal systems with different schemas and billing arrangements.

• Collaborate across organizational boundaries with research engineering, infrastructure, inference, and finance teams. Gather requirements from technical stakeholders, translate them into useful systems, and communicate trade-offs to non-technical audiences.

You May Be a Good Fit If You Have

• 5+ years of software engineering experience with a strong track record building and operating production systems. You write code every day — this is a hands-on engineering role, not a planning or coordination role.

• Kubernetes fluency at operational depth — you’ve operated production K8s at meaningful scale, not just written manifests. Comfort with scheduling, taints, labels, node management, and debugging cluster-level issues.

• Data pipeline engineering experience — designing, building, and owning the full lifecycle of production data pipelines. Experience with data warehouses (BigQuery preferred), schema management, streaming ingestion, SLOs for latency and completeness, and a strong instinct for correctness.

• Observability tooling experience — Prometheus, PromQL, and Grafana are in the critical path for this team. Experience writing recording rules, understanding metric semantics, and building monitoring systems that engineering teams actually rely on.

• Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable.

• Familiarity with at least one major cloud provider (AWS, GCP, or Azure) at the infrastructure level — compute, billing, usage APIs, cost management tooling. Multi-cloud experience is a strong plus.

• High autonomy and strong cross-team communication. You can gather your own requirements, navigate ambiguity, and work across organizational boundaries. Scrappiness and ownership matter more than polish.

Strong Candidates May Also Have

• Multi-cloud data ingestion experience — especially working with AWS and GCP APIs, billing exports, or vendor-specific telemetry formats. Experience normalizing data from external providers with different billing arrangements is directly applicable.

• Accelerator infrastructure familiarity — GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience working with ML training/inference systems at the hardware level.

• Performance engineering and benchmarking experience — building benchmark harnesses, establishing baselines, reasoning about compute efficiency (FLOPs utilization, memory bandwidth, interconnect throughput), and working with system teams to diagnose and improve performance.

• Data-as-product thinking — experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just building pipelines, but thinking about how platform data gets consumed.

• Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or large-scale ML environment. FinOps, chargeback systems, or infrastructure cost modeling.

Familiarity with ClickHouse, Terraform, or Rust. ClickHouse is the team’s current streaming store; Terraform for infrastructure-as-code; Rust for high-performance data collection agents.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.  

You will join the Cloud Infrastructure team in New York. The team designs, builds, and operates cloud platforms that support trading and research workloads, including digital asset and crypto-related systems. The team works closely with development, trading, and operations teams to deliver secure, reliable and scalable cloud solutions.

Your Future Role within QRT

• Design and implement deployment strategies for applications on AWS in collaboration with development, trading and operations teams
• Drive the adoption of CI/CD practices to automate and streamline software delivery
• Develop and maintain monitoring solutions to ensure availability, performance and reliability of cloud-based applications
• Work with developers to enhance application scalability, reliability and security in cloud environments
• Provide operational support and troubleshooting for issues related to cloud deployments and infrastructure
• Evaluate and introduce new tools and technologies to improve efficiency of DevOps processes
• Act as a liaison between engineering and business teams to facilitate effective communication and collaboration

Your Present Skillset

• Extensive experience with AWS services and infrastructure (e.g. EC2, S3, VPC and related components)
• Proficiency in scripting languages such as Python or Bash for automation
• Strong understanding of CI/CD principles and experience with pipelines using tools such as Jenkins or GitLab CI
• Experience with infrastructure-as-code tools such as Terraform, CloudFormation or AWS CDK
• Hands-on experience with distributed computing systems and processing large datasets
• Practical experience with containerisation and orchestration (e.g. Docker, Kubernetes)
• Good understanding of Linux systems, including networking and performance optimisation
• Familiarity with time synchronisation concepts and protocols such as NTP or PTP
• Strong communication and collaboration skills, with the ability to work effectively across teams and departments

Base salary range for this position is $150,000 to $240,000 per year. 

QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.  

The successful candidate will join the global Cloud Infrastructure team to design, build and support services and solutions to meet a wide variety of business requirements. You will be working closely with the trading, research and wider business teams to drive adoption of cloud-based services, implementing a cloud-first approach to problem solving. Cloud computing infrastructure is at the heart of QRT’s IT platform, and spans across many business areas including research technology, trading tools, market execution and data processing.

Your future role within QRT:

• Design and implement highly available, scalable, and secure cloud infrastructure on AWS
• Develop automation scripts to manage and maintain cloud infrastructure using tools such as Terraform and CloudFormation
• Monitor and optimize the performance and cost-effectiveness of cloud infrastructure
• Collaborate with development teams to support the deployment and operation of applications on AWS
• Evaluate and recommend new technologies to improve the reliability, scalability, and security of the company's cloud infrastructure
• Troubleshoot and resolve technical issues related to AWS infrastructure

Your present skillset:

• Extensive experience with AWS, including experience with EC2, S3, VPC, and other core services
• Proficiency with scripting languages (e.g. Python, Bash)
• Familiarity with configuration management tools (e.g. Ansible, Terraform)
• Experience with containers and orchestration technologies (e.g. Docker, ECS, Kubernetes)
• Experience with monitoring and performance tuning in a cloud environment
• Familiarity with agile software development methodologies
• Excellent communication and collaboration skills

Base salary range for this position is $150,000 to $220,000 per year. 

QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.

The role 

The Technical Director of Media and Entertainment, AI Infrastructure is a senior engineering leader who will initially operate as an individual contributor at the intersection of deep AI infrastructure engineering and the business of media and entertainment, with a clear path to building and leading a team as the business scales.

You will work alongside CTOs and engineering leaders at studio groups, VFX houses, gaming studios, agency holding companies, and generative AI model companies. Your role is not to pitch them; it is to build with them. You will translate their most complex infrastructure problems into engineered solutions, own the technical relationship with our most strategic ISV and cloud-native partners, and use what you learn in the field to directly influence the M&E product roadmap alongside Nebius's global Head of Product and Head of Engineering.

This is a ground-floor opportunity to define what AI-native infrastructure looks like for an industry in the middle of a fundamental transformation.

You are welcome to work remotely from the United States (SF Bay Area or NYC preferred) Travel expectations 10%-20% for executive meetings and key industry events. 

Your responsibilities will include: 

AI Infrastructure Architecture

• Own the Technical Blueprint: Personally architect the infrastructure solutions for our most strategic M&E partnerships , studio-scale content production pipelines, agency data consolidation plays, generative AI model deployments. These architectures must be engineered to survive real-world scale, not just pass a POC.
• The Physics to P&L Narrative: Fluently demonstrate to executive stakeholders how infrastructure decisions , data lake locality, storage tiering, inference optimization, directly impact their business model and operability.

Forensic Requirement Gathering

• Deconstruct the Bottleneck: Go beyond the stated problem to find the technical truth. Translate vague business goals (e.g., “We need lower rendering costs”) into precise engineering requirements (e.g., “We need to optimize the inference batch size on L40s to reduce cost-per-token by 30%”).
• Map the Transition: Identify exactly where a customer sits on the curve from legacy service bureau to AI-native tech platform and prescribe the specific infrastructure intervention needed to move them forward.

ISV & Partner Technical Strategy

• Build and Validate the Integration Layer: Identify, engage, and technically validate relationships with the most critical ISVs in the media and entertainment landscape, from rendering and VFX toolchains to generative AI platforms.
• Define the Standard: It is not enough to support these tools. You will define the reference architectures for how they run best on Nebius infrastructure, and work directly with ISV engineering teams to build and publish those standards.
• Decide What’s Worth Doing: In partnership with the GM, evaluate ISV and partner opportunities on their technical merit and strategic leverage , and be equally rigorous about what not to pursue.

Internal Technical Influence

• Shape the M&E Roadmap: Use forensic evidence from the field to prioritize and justify the M&E vertical roadmap. You will work directly with Nebius’s global Head of Product and Head of Engineering to translate partner and customer needs into product direction.
• Lead the M&E Product Summit: Chair a quarterly summit with Core Engineering leadership, using field evidence to drive roadmap decisions and maintain vertical momentum.

We expect you to have: 

• 12+ years of experience in cloud infrastructure, platform engineering, distributed systems, or a closely related technical domain.
• Executive Presence: Capable of commanding a room of engineers and presenting a layered technical roadmap to a C-Suite. You have operated at the top-to-top level , your counterparts are CTOs and VPs of Engineering.
• Builder Mentality: This role begins as a hands-on individual contributor position. You will architect and ship solutions alongside partners and build the assets (reference architectures, integration playbooks, technical frameworks) that make Nebius's M&E infrastructure strategy defensible and scalable. As the business case develops, this role is explicitly designed to grow into a team-building and leadership function, with the expectation that you will recruit, shape, and run that team. You may have come from a startup, run your own company, or operated within a large org in a way that felt like building from zero, and you know how to transition from maker to multiplier.
• Product-Minded: Experience defining a platform strategy, not just executing tickets. You are comfortable telling a customer “No” when a request creates technical debt, and proposing a better alternative.
• Ambiguity Tolerance: You thrive in environments where requirements are evolving. You do not wait for a roadmap; you build it.
• Forensic Mindset: You are not satisfied with surface-level answers. You dig into the kernel, the logs, and the P&L to find the truth.

AI Infrastructure Expertise

• Mastery of the Stack: Expert-level, production-grade knowledge of GPU architectures (H100, L40s), Kubernetes orchestration including Soperator, high-performance and parallel file systems (e.g., Lustre, WEKA), data lake architecture, and networking constraints (InfiniBand/Ethernet).
• Inference Optimization: You understand the nuances of model serving , batch sizes, quantization, KV caching, latency tradeoffs , and can architect solutions for both massive throughput and real-time (sub-50ms) demands.

Domain Context: Media & Entertainment

Industry Fluency: You have operated within the M&E ecosystem and can speak to the infrastructure implications across the following sub-sectors:

• Gaming
• Multimodal Generative Models
• AdTech
• VFX / Content Production

Non-negotiable: Candidates without deep, production-grade working knowledge of GPU infrastructure and inference-based solutioning will not be considered. This is a hard requirement, not a preference.

AI Infrastructure Expertise 

• Mastery of the Stack: You must be an expert in the physics of AI infrastructure. This includes deep, production-grade knowledge of GPU architectures (H100 vs. L40s), Kubernetes orchestration (K8s), high-performance storage parallel file systems (e.g., Lustre, WEKA), and networking constraints (InfiniBand/Ethernet). 
• Inference Optimization: You understand the nuances of model serving—batch sizes, quantization, KV caching, and latency tradeoffs—and can architect solutions for both massive throughput and real-time (sub-50ms) demands. 

It will be an added bonus if you have:

• Hands-on experience with VFX pipelines, studio-scale content production workflows, or the cloud tooling that powers them , render farm management, distributed simulation, asset pipeline tooling. You understand how content gets made, moved, and transformed at scale, and what infrastructure makes that possible.
• Strategic Empathy: The ability to distinguish between customers who need raw bare-metal access and those who need managed endpoints, and the wisdom to prescribe the right path.

Key Employee Benefits:

• Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
• 401(k) Plan: Up to 4% company match with immediate vesting.
• Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
• Remote Work Reimbursement: Up to $85/month for mobile and internet.
• Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage.

Compensation

We offer competitive salaries, ranging from $295k - $365k OTE (On Target Earnings) + Equity based on your experience.

Who We Are

EDO is the TV outcomes company. Our measurement platform connects convergent TV airings to the ad-driven consumer behaviors most predictive of future sales, helping advertisers, agencies, networks, streamers, and studios understand what works across linear and streaming TV.

We combine immediate engagement signals with decision science, vertical AI, and investment-grade data to help the advertising industry maximize media impact, optimize creative performance, and value every impression. EDO is headquartered in New York City and Los Angeles with office space in San Francisco. For employees residing full-time in NYC, SF, or LA, we have a hybrid work policy of three days in the office and two remote work days.

The Role

EDO is looking for a Senior Platform Engineer to help accelerate our shift toward a platform model. This is a senior IC role on the Infrastructure team focused on paved paths, reusable infrastructure patterns, and self-service workflows that help software, data, and machine learning engineers ship safely and efficiently.

Our environment is AWS-heavy and data-intensive, with heavy use of EC2, RDS, S3, SageMaker, MWAA/Airflow, Snowflake, dbt, Chef, Terraform, Spacelift, and emerging ECS/container patterns. The right person has strong AWS and infrastructure-as-code fundamentals, prior exposure to platform engineering practices, and the pragmatism to modernize existing systems without assuming everything should be rebuilt from scratch.

We approach infrastructure as an internal product: understanding engineers’ needs, prioritizing high-leverage platform capabilities, and iterating on tools and workflows that make teams faster, safer, and more self-sufficient.

What You Will Do

• Build and evolve EDO's internal platform capabilities: paved paths, reusable infrastructure modules, deployment standards, documentation, and self-service workflows.
• Own and improve Terraform and Spacelift-based infrastructure workflows, including module design, reviews, approvals, drift detection, and guardrails.
• Modernize existing AWS infrastructure, including EC2- and Chef-based systems, while helping teams adopt more standardized and repeatable patterns over time.
• Support production data and ML platform infrastructure, including MWAA/Airflow, Snowflake, dbt, SageMaker, S3, RDS, and related AWS services.
• Partner with software, data, and ML engineers as internal customers, turning recurring infrastructure needs into scalable platform capabilities rather than one-off support work.
• Improve deployment, CI/CD, observability, alerting, and incident response practices so teams can operate production systems with greater confidence.
• Expand pragmatic ECS/container deployment patterns where they create value, without treating Kubernetes as the default answer.
• Participate in a lightweight on-call rotation and use operational learnings to reduce toil, improve reliability, and strengthen the platform.

What We Are Looking For

• 6+ years of experience in platform engineering, infrastructure engineering, SRE, DevOps, cloud infrastructure, or similar roles.
• Experience building, operating, or contributing to an internal developer platform, infrastructure platform, developer productivity team, or similar platform-oriented function.
• Strong production experience with AWS, especially EC2, RDS, S3, IAM, networking, load balancing, and related operational patterns.
• Strong hands-on experience with Terraform or similar infrastructure-as-code tooling, including reusable modules and multi-environment patterns.
• Comfort working in a data-heavy environment and supporting technologies such as Airflow/MWAA, Snowflake, dbt, SageMaker, S3, and RDS.
• Product-minded approach to infrastructure: able to understand engineer pain points, prioritize high-impact platform work, document paved paths, and iterate based on adoption and feedback.
• Strong operational judgment, including debugging production systems, improving observability, and building platform patterns that support reliability, security, and cost efficiency.

Bonus Points

• Hands-on experience with Spacelift or similar IaC orchestration platforms such as Terraform Cloud or Atlantis.
• Experience helping an organization adopt platform engineering practices, including paved paths, golden paths, service templates, and developer-facing documentation.
• Experience with Chef, AWS cost management, security/compliance-driven infrastructure, or production ML/data science infrastructure.

Compensation and Benefits

EDO offers a competitive compensation package. Components of compensation include:

• Mid-stage equity and competitive salary
• Flexible Time Off
• Medical, dental and vision coverage: EDO provides full coverage for individual medical plans and partial coverage for dependent or family plans.
• 401(k) plan, FSA, HSA
• Commuter Benefits
• When in an office, employee meals, snacks, and more

In compliance with New York and California Pay Transparency Law, the salary range for this position is $170,000 to $190,000 plus equity. We note the salary information as a general guideline only, as actual compensation may vary from posting. We will consider various factors to determine the offer for this role, including the scope and responsibilities of the position, relevant work experience, key skills, training, and business considerations.

EDO is an Equal Opportunity Employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status. All your information will be kept confidential according to EEO guidelines.

WHO WE ARE

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that unifies identity, intelligence, and omnichannel activation into a single platform – powered by trillions of consumer signals and one of the industry’s largest proprietary databases. Our enterprise clients use the Zeta Marketing Platform (ZMP) to personalize experiences at the individual level across every channel. 

THE ROLE

Our Vertical Applications team builds web applications that bring the power of ZMP to specific industries – Healthcare, Political, Retail, and more. Every vertical comes with its own fascinating challenges: unique compliance requirements, distinct data models, and workflows that genuinely matter to the people using them. It’s the kind of work where you get to learn new domains, solve real problems, and see your applications make a tangible impact. 

You’ll own applications end-to-end: partner with product owners to define the problem, architect the backend, integrate with Zeta’s core platform, build the frontend, ship to production, and ensure operational excellence. We value clean, simple architectures, test-first development, and continuous delivery. AI-assisted development with tools like Cursor, Claude Code, Gemini and Codex is embedded in our everyday workflow, and we’re excited about what agentic engineering unlocks for both development velocity and software quality. 

What You’ll Do 

• Own vertical web applications from idea to production – working closely with product owners, designing the architecture, building it, shipping it, and running it. 

• Architect backend services (Python, Java, Ruby, Node.js) with a focus on simplicity and reusability across verticals, so good patterns compound over time. 

• Build polished frontend experiences in React/TypeScript/Ant Design System that connect seamlessly with backend APIs (REST, Thrift). 

• Ship continuously and confidently through CI/CD, with observability, resilience and reliability built in from the start. 

• Use AI-assisted development tools as a natural part of your workflow to move faster while keeping quality high. 

• Weave AI/LLM capabilities into vertical applications, opening up new possibilities for each domain. 

• Collaborate across teams – mentor fellow engineers, lead technical initiatives, and bring clarity to complex decisions for both technical and non-technical audiences. 

What We’re Looking For 

10+ years of software engineering with a history of owning and operating the systems you build. You’re deeply proficient in at least two of Python, Java, Ruby, or Node.js, with solid React/TypeScript skills on the frontend. Continuous delivery, test-driven development, agile and shift-left are things you genuinely practice – not just checkboxes on a process document. 

You’re comfortable building and operating scalable, distributed, high performant systems and navigating multi-tenant, compliant environments. You’re already using AI-assisted coding tools (Cursor, Claude Code, Gemini, Codex, or similar) and you’re curious about pushing those workflows further.  

You’re a strong communicator who enjoys working directly with product owners, proposing architectures, building consensus across teams, and then making it happen. You’re energized by learning new domains and collaborating with people who care about their craft. 

Nice to Have 

• MarTech or AdTech experience (DSPs, bid stream processing, data-intensive platforms). 

• Domain knowledge in Healthcare, Political, or Retail verticals. 

Tech Stack 

Why You’ll Love It Here 

• Interesting problems across diverse verticals – Healthcare, Political, Retail – on a platform processing trillions of consumer signals. You’ll never be bored. 

• AI-native engineering culture – agentic development isn’t a side experiment, it’s how we build. You’ll be at the forefront of how software teams work in the future. 

• Real ownership and autonomy. We trust our engineers to make great decisions and give them the space to do it. 

• Collaborative, low-ego team that genuinely enjoys working together and learning from each other. 
• Public company (NYSE: ZETA) with strong growth, competitive compensation, equity, and comprehensive benefits. 

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $200,000 - $220,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-YW1

Quant Library Developer, Macro Technology.

A Career with Point72’s TECHNOLOGY TEAM

As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications.

As a member of Point72’s Technology team, we encourage and support your professional development from day one, helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity; all while delivering real business impact for our multi-billion-dollar global business.

What you’ll do

• Design, build, and extend core C# analytics services, APIs, and libraries used across the Macro business.
• Develop and operate high-performance distributed systems with strong guarantees around correctness, latency, and scalability.
• Build real-time and historical analytics services supporting pricing, risk, and global market data workflows.
• Design and maintain time-aware (historical and real-time) data models and services, ensuring consistency across analytics use cases.
• Develop and integrate derived data pipelines and datasets used in research, backtesting, and production analytics.
• Contribute to API design, data modeling, and system architecture for shared analytics platforms.
• Integrate analytics services with batch and streaming data pipelines across research and trading workflows.
• Partner closely with quants and portfolio managers to translate investment requirements into robust platform capabilities.
• Contribute to system reliability through testing, monitoring, and operational best practices.
• Participate in code reviews and technical discussions to improve design, performance, and maintainability.

What’s REQUIRED

• 3–10 years of experience developing production-quality backend software in C#, with a strong focus on distributed systems and APIs (REST/gRPC).
• Proven experience designing, deploying, and supporting backend services or platforms in cloud or hybrid environments .
• Strong understanding of distributed system design, including data modeling, consistency, and time-series or event-driven architectures.
• Hands-on experience with streaming and messaging systems, such as Kafka, and building scalable data pipelines with derived data generation and persistence.
• Familiarity with containerized environments, such as Kubernetes, and modern data and storage technologies.
• Solid grasp of SDLC best practices, including testing, code coverage, monitoring, and operational support in production systems.
• Experience with Python and exposure to C++, particularly in performance- or analytics-oriented contexts.
• Awareness of financial markets and instruments, including rates, FX, and derivatives, and how pricing and risk analytics are applied.
• Strong communication and collaboration skills, with the ability to work closely with investment professionals.
• Commitment to the highest ethical standards.

We take care of our people

We invest in our people, their careers, their health, and their well-being. When you work here, we provide:

• Fully paid health care benefits
• Generous parental and family leave policies
• Volunteer opportunities
• Support for employee-led affinity groups representing women, people of color and the LGBT+ community
• Mental and physical wellness programs
• Tuition assistance
• A 401(k) savings program with an employer match and more

About Point72

Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth. For more information, visit https://point72.com/.

The annual base salary range for this role is $245,000-$300,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.

Senior Fullstack Software Engineer - Experiences

Location: Soho, NYC / Remote
Department: Engineering

The Role

We’re looking for a Senior Fullstack Software Engineer to help architect, build, and scale the next generation of our Flowcode 2 Consumer Experiences. You will join our Experiences pod with a focus on creating amazing end user hub and landing page experiences that are dynamic and engaging. You’ll work across the stack — from contributing to backend services to building out dynamic end to end landing pages. Though this is a full stack position, we are looking for someone that has deep backend experience as well.

As one of the senior engineers on a small but highly capable team, you’ll own medium to large sized features, drive technical execution, contribute to a delivery focused environment, and mentor others. You’ll balance hands-on engineering with architectural thinking, helping us move fast while maintaining reliability, performance, and code quality.

This is an ideal role for a problem-solver who values simplicity over complexity, enjoys building dynamic and interactive applications and approaches engineering with pragmatism and curiosity.

What You’ll Do

• Design, build, and maintain scalable features across a modern front-end framework and backend services.
• With support, own key features end-to-end, from data design to user-facing experiences.
• Architect for growth — help drive your pods’s technical roadmap and shepherd established engineering best practices.
• Collaborate across teams with product, design, and data to deliver measure, deliver and grows features quickly and iteratively.
• Write clean, reliable, and maintainable code, with strong attention to performance, best practices and developer experience.
• Mentor engineers and help elevate technical execution across you pod.
• Stay pragmatic — balance ideal engineering with the realities of speed, customer needs, and startup resource constraints.
  
  

What We’re Looking For

• 5–7+ years of experience building and shipping production-quality software across the stack.
• Proficiency in at least one modern backend language (e.g., Go, Python, C#,, Java).
• Strong experience with React, Next.js, or other modern front-end frameworks. We use Svelte but any modern framework experience is welcome.
• Deep understanding of web architecture, API design, and data modeling in relational and/or NoSQL databases.
• Familiarity with cloud environments (AWS, GCP, or similar) and containerized deployment (Docker, Kubernetes).
• Commitment to code quality, with solid grounding in design patterns, testing, and CI/CD.
• Strong grasp of scalability and performance — able to make informed tradeoffs between speed and correctness.
• Excellent communication skills and a collaborative mindset.
• A builder’s mentality — comfortable taking initiative and owning outcomes from design through production.

Nice to Have

• Experience building consumer focused SaaS applications and experiences
• Experience with form based, dynamic applications with rich user generated content.

Flowcode is not for everyone. We hire with a pinhole lens — only those with the rare combination of intellectual horsepower, execution velocity, and uncompromising drive will thrive here. If you are seeking to operate at the highest levels of performance and impact, we want to meet you.

How to Apply

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

A successful candidate’s starting pay will be determined based on the role, job-related skills, experience, qualifications, work location, and market conditions. The current range for this role is up to $200-$220k plus equity. 

Staff Software Engineer - Platform

Location: Soho, NYC / Remote
Department: Engineering

The Role

We’re looking for a Staff Software Engineer to help grow and build the core platform that powers our Flowcode 2 application at scale. This role sits at the intersection of architecture, leadership, and pragmatic execution with a focus on creating and augmenting reliable, scalable, and extensible services and applications. 

You’ll operate as a technical leader with in our Platform pod, growing platform capabilities, building new features and problem solving in a dynamic and challenging technical environment.. While this is a hands-on role, it requires a strong bias toward backend systems, distributed architecture and deep technical leadership. We value the ability to guide teams toward pragmatic, high-impact solutions.

This role is ideal for an engineer who values simplicity, correctness, and pragmatism, and who can balance long-term platform investments with immediate business needs.

What You’ll Do

• Own critical systems end-to-end, including design, implementation and deployment,
• Hands on designing, building, and maintaining scalable features across a modern front-end framework and backend services.
• Architect for growth — help drive your pods’s technical roadmap and shepherd established engineering best practices.
• Collaborate across teams with product, design, and data to deliver measure, deliver and grows features quickly and iteratively.
• Mentor and guide senior engineers, raising the bar for technical execution and system design across teams.
• Balance ideal engineering with the realities of speed, customer needs, and startup resource constraints.
• Drive improvements in observability, performance, and incident response
• Advocate for pragmatic solutions, solving the right problems with the appropriate level of complexity.
  
  

What We’re Looking For

• 8+ years of experience building and operating production-grade systems, with a strong backend focus.
• Deep expertise in building high-performance, concurrent services.
• Proven experience designing and scaling distributed systems and service-oriented architectures.
• Strong understanding of API design, data modeling, and consistency tradeoffs Experience with cloud infrastructure (AWS, GCP, or similar) and modern deployment patterns (Docker, Kubernetes).
• Proficiency in several modern backend language (e.g., Go, Python, C#,, Java).
• Commitment to code quality, with solid grounding in design patterns, testing, and CI/CD.
• Strong grasp of scalability and performance, able to make informed tradeoffs between speed and correctness.
• Excellent communication skills and a collaborative mindset.
• A builder’s mentality, comfortable taking initiative and owning outcomes from design through production.
• A history of working with in 20+ person engineering organizations and collaborating with Product and Design to enable feature delivery at a reasonable velocity

Flowcode is not for everyone. We hire with a pinhole lens — only those with the rare combination of intellectual horsepower, execution velocity, and uncompromising drive will thrive here. If you are seeking to operate at the highest levels of performance and impact, we want to meet you.

How to Apply

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

A successful candidate’s starting pay will be determined based on the role, job-related skills, experience, qualifications, work location, and market conditions. The current range for this role is up to $280-$310k plus equity. 

Atlas Growth is a cloud engineering group whose mission is to guide customers through their app development journey—from cluster configuration, data modeling and load testing, to running a production workload at scale. We use an in-house experiments platform which helps us validate our features quickly, releasing only the work that positively impacts our customers. Our engineers participate in cross-functional “squads” with product, design, analytics, and research focusing on a single metric (e.g. retention). Our engineering team is part of a larger Atlas Core Engineering org, building foundational elements of MongoDB’s developer data platform.

Atlas Growth 2 builds customer-facing features in Atlas and sits alongside other Growth engineering teams. Recent projects include an AI Chatbot for cluster creation, a recommendation system that offers tips for better database performance, and a pricing page designed to optimize conversion rates.

This position is based in our New York City office and open to our “Flexible” or “In Office” working models.

Role Overview

Atlas Growth 2 seeks a Senior Software Engineer. Senior engineers lead complex projects, provide mentorship to teammates, and shape the technical direction of our team. They are expected to proactively suggest and implement improvements to our product, processes, and infrastructure, in addition to leading their projects.

Candidate Profile

• 6+ years of software engineering experience
• Fluency in TypeScript and JavaScript
• Proficiency in Java, Go, C++/C, or a similar compiled language
• Experience writing database queries and indexes—either document-based or relational
• Experience writing and reviewing technical specs 
• Interest in A/B testing or product design
• Familiarity with Kubernetes and container architecture
• Track record of designing, releasing, and monitoring highly complex features
• Experience with on call rotations

Expectations

• Contribute readable, well-tested, and debuggable code
• Work closely with product management to assess feasibility of upcoming projects and guide long-term roadmap of customer-facing features
• Write scope and technical spec docs for large projects assigned by your manager. Lead small working groups of two or three engineers for these projects
• Provide well-reasoned, thorough review of the team’s code and technical documentation
• Take ownership of a particular domain and make a plan to improve that area
• Offer informal mentorship to your peers
• Participate in our 24/7 on-call rotation shared across all Growth teams

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions 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.

Req ID: 1273369973

MongoDB’s Storage Layer Services (SLS) team is re-architecting the MongoDB cloud storage layer and sits at the heart of our next-generation cloud storage architecture. This relatively new team is building performant, multi-tenant distributed storage services that both enhance today’s Atlas storage stack and enable more customer workloads to run more efficiently.

As the Lead Site Reliability Engineer for SLS, you will partner with the teams building these storage services to define SLOs, shape capacity plans, and ensure the reliability, durability, and operational safety of the storage layer that underpins Atlas. You’ll help grow and lead a small, senior team of SREs as founding members of this organization, playing a crucial role in executing on a multi-year roadmap for MongoDB’s cloud storage architecture.

We are looking to speak to candidates who are based in Dublin for our hybrid working model.

Responsibilities

• Build and lead a team of 6-8 engineers, fostering a positive culture, handling career growth and performance conversations, and proactively removing blockers
• Define and drive a clear technical vision and comprehensive roadmap for our multi-tenant distributed storage systems, balancing long-term strategic infrastructure goals with immediate engineering needs
• Contribute through hands-on technical work, such as leading architectural design reviews, reviewing PRs, and stepping in to guide the team through complex operational challenges
• Act as the primary liaison for the Storage Layer Services SRE team, collaborating closely with other engineering leaders to ensure platform alignment and manage stakeholder expectations

You may be a good fit if you

• Have 10+ years of experience working on software and operating distributed systems, with 2+ years managing engineering teams
• Possess a customer-focused mindset, treating internal developers as your primary users
• Value efficiency in processes and operations, and have a track record of optimizing team workflows
• Prefer automation over manual processes, fostering a culture of building software solutions to eliminate toil
• Have deep technical familiarity with Kubernetes ecosystems, containerization technologies, and modern IaC tooling (e.g., Terraform, Crossplane, or Operators) so you can effectively guide the team's technical decisions
• Have operated or supported stateful storage or database systems at scale and are comfortable with durability, consistency and recovery trade-offs
• Excel at translating complex business and engineering requirements into actionable, phased technical roadmaps
• Have a high level of empathy, responsibility, ownership, and accountability
• Excellent verbal and written technical communication skills

Strong candidates may also have experience with

• Leading major architectural shifts, such as moving from legacy storage stacks to new multi-tenant storage architectures, including planning and executing large-scale data and workload migrations with tight availability and durability requirements
• Managing and scaling infrastructure across multi-cloud environments (AWS, GCP, or Azure)
• Designing secure, multi-tenant runtime environments at scale

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

Req ID: 1273396229