The Cloud Automation Engineer designs, builds, and operates automation-first cloud infrastructure platforms using Infrastructure-as-Code (IaC), CI/CD, and serverless automation. The role enables secure, repeatable, and resilient cloud environments through standardized automation, self-service capabilities, and codified governance primarily in Microsoft Azure, with tertiary exposure to AWS. 

This role partners closely with Cloud Platform Engineering, Security, Network, and Operations teams to ensure all automation solutions are secure-by-design, private-network-first, and resilient by default, including full lifecycle support for business continuity and disaster recovery (BC/DR) implemented through IaC. 

What will you do?

​​Infrastructure-as-Code (IaC) & Cloud Automation 

• Design, develop, and maintain Infrastructure-as-Code using Terraform, ensuring infrastructure is reproducible, testable, and auditable. 
• Build and maintain reusable IaC modules aligned with platform standards, security guardrails, and network architecture patterns. 
• Implement automated provisioning, configuration, scaling, and decommissioning workflows for cloud infrastructure and shared services. 
• Define and maintain code repositories following industry BEST PRACTICES and strong code repository governance 
• Design and maintain BC/DR capabilities and recovery environments using Infrastructure-as-Code.  
• Automate recovery environment deployment and support validation/testing routines to ensure recoverability and resilience. 

CI/CD Pipeline Engineering  

• Design, implement, and maintain CI/CD pipelines for infrastructure and platform automation. 
• Integrate testing, validation, and policy enforcement into pipelines to promote safe and consistent changes. 
• Enable repeatable deployments across environments using modern DevOps practices. 

​​​​Azure Automation & Serverless Engineering 

• Build automation solutions using PowerShell, Azure Logic Apps, Azure Automation Accounts, and Azure Functions. 
• ​Develop event-driven and scheduled automation for platform operations, governance processes, and operational workflows. 
• ​Implement robust secret management and secure runtime configuration practices. 
• ​Develop and maintain automation using PowerShell, Python, and Bash scripting.  
• ​Use appropriate scripting/tools to enable orchestration, integration, validation, and operational automation across platforms.

​​Collaboration and Support​ 

• Work closely with other IT teams to integrate cloud network solutions with existing systems and applications. 
• ​​Troubleshooting, diagnosing, and resolving hardware, software, and other network and system problems including router, switches, firewalls, wireless controllers and VPN concentrators. 
• ​Maximizing network performance by monitoring activity and utilizing observability tools such as Dynatrace and Azure monitoring. 
• ​Monitoring and maintenance of company-wide AV (Audio-Video) infrastructure – such as conference rooms, collaboration spaces etc.  
• ​Serve as the on-call network engineering for after-hours escalation issues as part of the company on-call rotation schedule.​ 

Modern Observability & Operational Telemetry ​ 

• Ensure automation solutions are observable and operationally supportable by integrating with modern observability platforms such as Dynatrace, Datadog, and Azure-native tooling including Azure Monitor and Azure Log Analytics. 
• Develop dashboards, alerts, and operational insights, enabling faster detection and root-cause analysis (RCA) by using telemetry (metrics/logs/traces) and platform standards. 
• Use modern query languages such as DQL (Dynatrace Query Language) and KQL (Kusto Query Language), with secondary knowledge of SQL, to support troubleshooting, insights, and automation-driven operations

Security & Compliance Engineering

• Embed cloud security and technology security best practices into all automation solutions (identity, secrets, least privilege, logging, secure configuration baselines). 
• Partner with Security teams to ensure automation aligns with enterprise security requirements and audit expectations. 
• Ensure changes are traceable and auditable through source control and deployment records. 
•  Apply a strong foundation in cloud network theory to ensure automation processes are designed with a private networking first priority.  
• Ensure automation supports secure connectivity patterns (segmentation, routing considerations, controlled ingress/egress, and service endpoint/Private Link-style design patterns where applicable). 

What will you need to succeed in this role?

• Undergraduate degree in Engineering or related field with ​​one of the Certifications: AZ-104, AZ-400, Terraform Associate or Terraform Authoring and Operations Professional​ 
• Minimum of 5 years of experience with batch scripting languages 
• ​Minimum 3 years of experience with technology process automation using tools such as Azure Functions, Logic Apps, Automation Accounts, Lambda or Power Platform 
• ​Minimum 2 years DevOps experience 
• ​Relevant certifications such as AZ-104, AWS CloudOps Engineer  
• ​AZ-400 certification is highly desirable  
• ​Minimum of 3 years of experience with Infrastructure as Code technologies such as Azure BICEP, ARM or Terraform. Preference to direct Terraform experience. 
• ​Minimum of 2 years of experience with private cloud networking concepts
• Technical Expertise: Proficiency in infrastructure technology automation, working within cloud platforms such as AWS, Azure, or Google Cloud.
•  In-depth understanding of system automation scripting technologies using common scripting languages such as PowerShell, Bash or Python.  
• ​​In-depth understanding of high availability, disaster recovery, multi-site architecture, serverless micro-service automation architecture, and hybrid cloud service integration is a must.​
• ​Infrastructure as Code Knowledge: Strong understanding of Infrastructure-as-Code concepts and technologies (e.g. Terraform, BICEP, ARM, Git).
• Ability to build Terraform code based on technology infrastructure architecture designs and service catalogue standards.
• Knowledge of Git repository branch strategies and code repo best practices.
• Automation and Integration Skills: Experience with serverless automation tools across hybrid cloud providers to build integration and automation processes based on business need.
• ​Hands-on experience with serverless automation tools such as Azure Automation Accounts, Logic Apps, Functions, AWS Lambda and Data Factory.
• Strong understanding of object-oriented scripting using common script languages like PowerShell, Bash or Python.
• Working experience with vendor API tools for use within automation and integration processes.
• ​Problem-Solving: Ability to diagnose and resolve complex micro-service and CI/CD issues.
• Ability to diagnose and resolve complex micro-service and CI/CD pipeline issues across a hybrid cloud environment.
• Act as SME and tier 3 support for troubleshooting of deployed automation and integration solutions.
• Solving and conducting disaster recovery operations when required
• Communication: Excellent verbal and written communication skills to collaborate effectively with team members and stakeholders.
• ​Project Management: Ability to manage multiple projects and prioritize tasks effectively. 

#LI-Hybrid

The expected base salary range for this position is $64,500 - $114,500. Depending on your relevant experience, skills, qualifications, market conditions and business needs, base compensation may vary. You have the potential to earn more through Gore Mutual’s discretionary bonus program which gives you an opportunity to increase your total compensation, provided the business meets its performance targets and you meet your individual goals.

Please note: This range reflects the expected base salary for this role but may not represent the full compensation range for all experience and skill levels. During the recruitment process, we will discuss and consider how your unique qualifications align with the broader range for this position.

Gore Mutual is proud to offer a comprehensive total rewards package which includes extended health and dental benefits, disability insurance, retirement plan matching, paid time off, recognition and perk programs.

#LI-Hybrid

​​Cloud Engineer is a key role as this will automate, evolve, and establish a scalable cloud platform across the company optimizing for self-service and governance. The role will work with both Cloud Native platforms Azure and AWS, leverage tools like Kubernetes (AKS), and Cloud Hosting providers offerings like IaaS, PaaS, and SaaS ensuring consistent experience and high standards are established.

What will you do?

​​Maintain Microsoft Azure cloud infrastructure​ 

• ​​Utilize best practices to ensure backup and recovery techniques for applications on Azure platform. 
• ​Supporting and maintaining Azure cloud infrastructure 
• ​Implementing deploying workloads on Azure virtual machines 
• ​Container technologies i.e. Kubernetes & AKS  
• ​Utilize Terraform code to deploy multiple resource groups, VMs, and VNETs 
• ​Upgrading version and certificates  
• ​Load Balancers, AzurePolicies, AzureKayVault and Tagging 
• ​Expertise in Microsoft Azure Cloud services (SaaS, PaaS and IaaS) 
• ​Monitoring Azure infrastructure and logs 

​​Maintain Azure cloud AKS​  

• ​​Administration of AKS clusters 
• ​Configuring web apps, Azure App services, Azure DNS, Azure traffic manager, App services and Azure Application gateway, 
• ​Managing the Azure Kubernetes Services policies, providing access to different Azure resources ​managing secrets, firewalls, PODS, containers. 
• ​Injecting data in applications  
• ​Troubleshooting cluster related issues
• ​Cluster AutoScaler and load balancers for Azure Kubernetes Service (AKS) using Terraform and worked with scheduling deploying, and managing pods and replicas in AKS
• Working knowledge in deploying CI/CD system using Azure DevOps and Kubernetes container environment​ 

Azure Automation

• ​​Good knowledge of building and supporting CI/CD pipelines using Azure DevOps 
• ​Creating Ansible play books, Dockers and Jenkins 
• ​Working knowledge on json, yaml, Terraform and Helm chart​ 

After-Hours Support 

• Participate on an on-call rotation and be available for out of office hours support when needed 

What will you need to succeed? 

• Undergraduate degree in Information Technology with MS or AWS Cloud Certification desirable
• 3-5 years of hands-on experience in Azure AKS
• Minimum 3 years of good knowledge in building and supporting CI/CD pipelines using Azure DevOps
• Minimum 4 years Azure Cloud Platform
• Minimum 2 years Azure DevOps experience
• Proficient in Administrating Azure laaS/PaaS, Azure Virtual Machines, VNET, Network services, Azure DevOps,
• Hands on experience on SQL Databases, Storages, AzureActive Directory, Monitoring, Autoscaling,
• Hands on experience in Azure Blueprint, Azure Site Recovery and Azure backup
• PowerSheII Automation, Azure Search, DNS,VPU extensive
• 4+ years’ working experience of Azure SQL and Cloud platform
• Strong understanding of Terraform
• Hands on experience on Load Balancers, AzurePolicies, AzureKayVault and Tagging
• Expertise in Microsoft Azure Cloud services (SAAS, PASS and IAAS)
• Monitoring Azure infrastructure and logs
• Strong knowledge of Azure Networking, Azure Virtual Machines, Azure Active Directory
• Experience with Load Balancers, AzurePolicies, AzureKayVault and Tagging
• Experience with Cloud and other traditional monitoring technologies, as well as hands on experience instrumenting alerts based on aggregated logs and analytics output.

#LI-Hybrid

The expected base salary range for this position is $64,500 - $114,500. Depending on your relevant experience, skills, qualifications, market conditions and business needs, base compensation may vary. Please note: This range reflects the expected base salary for this role but may not represent the full compensation range for all experience and skill levels. During the recruitment process, we will discuss and consider how your unique qualifications align with the broader range for this position.

About Graphcore

At Graphcore, we’re building the future of AI compute.

We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.

As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem. To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.

We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

The Person 

Graphcore’s experienced, skilled, and motivated engineering team is heavily involved in shaping the future of AI. A successful candidate will exhibit exceptional knowledge in Design for Testability (DFT) and will have a strong technical background and experience in DFT methodologies, complemented by a robust, self-motivated work ethic. The ideal candidate should also have a focus on quality and demonstrate a good understanding of the importance of production test on the success of a product. Some hands-on experience in one or more of the following areas is essential: RTL design, simulations and debugging, synthesis, STA.  

The Role: 

We are expanding and looking for an experienced DFT engineers to join the Silicon team. As a part of our team, you will have the opportunity to work on next-generation AI designs targeted for data centers applications. 

Responsibilities: 

• Keep up with the latest industry trends in DFT domain and help adopt the latest DFT techniques and methodologies 

• Work closely with design, verification, physical design and product engineering teams to integrate DFT requirements into the overall design process 

• Define and implement DFT architecture and features for next-generation AI designs and support their verification effort 

• Develop efficient DFT flows and methodology compatible with silicon design flows 

• Work with 3rd party IPs to integrate the provided design into the DFT infrastructure 

• Generate structural test vectors, analyze and improve test coverage 

• Work with the product and test engineering teams to ensure successful silicon bring-up and help identify any silicon failures to enhance yield learning and improvement 

Requirements: 

• Very good understanding of DFT components like JTAG (IEEE 1149.x), IJTAG (IEEE P1687), Core Test (IEEE P1500), SSN (Streaming Scan Network), Test Compression, OCC etc. 

• Experience on developing DFT specifications and driving the implementation of the DFT features 

• Experience in MBIST and BISR implementation and verification is desired 

• Solid understanding of design verification methodologies for validating the DFT features using simulation in pre-silicon designs 

• Exposure to STA constraints development and analysis for DFT modes and SDF simulations would be a plus 

• Experience in Scan based testing and industry standard ATPG tools 

• Knowledge of ATPG pattern verification and gate-level simulation flows using Synopsys VCS and Verdi or other EDA tools 

• Very good knowledge of Digital Integrated Circuits and Systems 

• Hands-on experience with Verilog RTL coding and familiarity with System Verilog   

• Strong scripting and debugging skills using programming languages like Python, TCL, Perl, Shell etc. 

• Exposure to silicon bring-up, post-silicon testing and tester pattern debugging 

• Strong problem-solving skills across various levels of design hierarchies 

• Great team working and communication skills 

Academic Credentials 

• Bachelors or Masters or PhD in Computer engineering/Electrical engineering/Electronics Engineering

Benefits: 

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments  

We welcome people of different backgrounds and experiences and are committed to building an inclusive work environment that makes Graphcore a great home for everyone. We are an equal opportunity employer and want to build a work environment where everyone is happy, productive and respectful so they can do their best work. If you have a disability or additional need that requires accommodation, just let us know. 

About Graphcore

At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary 

As a hardware signal integrity engineer you will develop, extract and simulate PCB structures to ensure that the high speed SERDES (112Gbps) and DDR interfaces perform correctly within the system budget. 

You will work closely with the PCB and package substrate CAD engineers to design component signal launches from BGA components and connectors, layer transition via structures, and cable interconnect. You will define the low-loss materials to be used for future designs and work closely with Graphcore’s system architecture team and suppliers to ensure the best possible performance is achieved. You will be an expert user of high-speed PCB simulation tools and be familiar with industry best practice in high-speed digital system design.

The Team

Graphcore’s Hardware Engineering Team creates both products for sale in volume production and hardware test & validation systems based on Graphcore’s IPU processor.

These systems allow Graphcore’s customers to develop leading-edge machine-leaning solutions for training and inference.

Responsibilities and Duties

Signal and Power Integrity specialist for the development of production systems and test boards for Graphcore’s family of processors.
Includes:

• Development of printed circuit board structures for high frequency (112Gbps, 16Gbps) SERDES interfaces, DDR interfaces 
• PCB stackup definition
• System, PCB and substrate level simulation and analysis of signal and power integrity
• Graphcore Integrated Circuit device interface requirements definition, tool & vendor relationships
• PCB design requirement and constraint definition, PCB layout supervision
• Prototype bring-up, evaluation, validation & system test

Candidate Profile 

• 5+ years’ experience in high-speed digital circuit development, with a deep understanding of signal and power supply integrity
• Knowledge of high-speed circuit design requirements to ensure signal integrity and robust rejection of interference and crosstalk is essential
• Experience of high frequency (tens of GHz) SERDES design and validation
• Experience with ANSYS SIWave, HFSS, and/or Mentor Hyperlynx Signal and Power Integrity tools
• High speed processor system design with experience in interfaces such as SERDES, PCI, DDR, Ethernet, etc.
• Design of BGA & connector pad launches, via structures and transmission lines for GHz signals.
• This position will require extensive practical work in the lab, bringing up, debugging and validating designs
• Expertise in the use of vector network analysers, high speed digital oscilloscopes, signal generators
• A rigorous approach is required to make sure designs will work correctly the first time
• Independent working and the taking of responsibility, with excellent cooperative and communications skills to work in a small team environment
• Experience working in a small team, which requires a wide range of skills, an eagerness to participate in all parts of the development cycle from concept to testing in the lab and supporting manufacture and customers. 

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Your Impact at LILA

Lila is seeking a motivated SCADA Engineer to contribute to the design, development, and implementation of control systems for automated scientific equipment. This role involves applying core engineering principles to support PLC controls, robotics integration, troubleshooting systems, and collaborating within cross-functional teams to enhance laboratory automation.

What You'll Be Building

• Assist in designing, programming, and deploying control systems using PLC and SCADA technologies to optimize laboratory workflows.
• Support the integration and testing of advanced robotics and conveyance systems within existing automation frameworks.
• Assist in integrating 3rd party equipment and vendor software into SCADA and make custom HMIs to aid in user controls.
• Contribute to the design and implementation of safety systems to safely operate a mix of lab equipment and robotics.
• Collaborate with software teams to support the integration of control systems with broader IT/OT factory infrastructure.
• Create, update, and maintain engineering documentation, including P&ID diagrams, wiring schematics, control narratives, and instrument IO lists.
• Support multi-team automation projects by independently executing technical tasks, meeting milestones, and adhering to engineering best practices.
• Perform calibration, testing, troubleshooting, and validation of control systems to ensure they meet performance, accuracy, and safety standards.
• Work closely with subject matter experts (SMEs) and project teams to understand technical requirements and solve moderately complex hardware/software challenges.
• Identify recurring technical issues and implement improvements to enhance system reliability and operational efficiency.

What You’ll Need to Succeed

• 2–4 years of experience in designing, implementing, or maintaining control systems, preferably in automated manufacturing or laboratory environments.
• Solid understanding of PLCs, HMI, SCADA, and related automation software and hardware.
• Familiarity with industrial networking basics in OT deployments (e.g., IP addressing, basic routing).
• Experience reading and creating detailed engineering documents and schematics using tools like AutoCAD, SolidWorks Electrical, or similar.
• Hands-on experience or academic background in robotics integration and programming.
• Effective communication and collaborative skills for working within project teams and with internal stakeholders.
• Strong analytical and problem-solving skills, with the ability to independently execute solutions for well-defined technical issues.

Bonus Points For

• Ignition SCADA Core training and HMI design experience.
• Structured text programming experience in TwinCAT, Python, C++, etc.
• Familiarity with communication protocols like OPC-UA, MQTT, and REST APIs.
• Exposure to safety system design concepts and classifications like SIL or PL.
• Basic understanding of managed network switches, port addressing/IP subnetting, and DHCP services.
• Ability to troubleshoot basic traffic flows between OT networks and cloud instances.

Your Impact at LILA

As a Principal Security Engineer focused on AI Security, you will define and drive the technical strategy for securing how AI is used across Lila's enterprise. You will operate as a senior individual contributor, partnering with IT and business teams to ensure safe and compliant adoption of AI tools and platforms.

While Lila builds AI-powered systems, this role is primarily focused on securing the use of third-party and internally deployed AI tools across the enterprise — ensuring sensitive data, intellectual property, and scientific workflows are protected as AI becomes deeply embedded in how work gets done.

What You'll Be Building

• Enterprise AI Security Strategy — Define and implement security controls and guardrails for the use of AI tools (e.g., LLM APIs, SaaS AI platforms, and internal AI services) across the organization.
• AI Gateway & Agentic Gateway Security — Design and implement AI gateway controls to manage and monitor access to external and internal AI systems. Secure agentic workflows by enforcing identity, authorization, tool-use constraints, and policy controls for autonomous or semi-autonomous agents.
• AI Red Teaming & Adversarial Testing — Conduct red teaming and adversarial testing focused on enterprise AI usage, including prompt injection, data exfiltration, jailbreaks, and abuse of connected tools and plugins.
• Data Protection for AI Usage — Develop and enforce controls to prevent sensitive data leakage through AI systems, including input/output filtering, data classification, tokenization, and secure handling of prompts, embeddings, and outputs.
• Multi-Layer AI Security (Network, Endpoint, Data) — Integrate AI security into existing enterprise security layers: network visibility and control over AI service access, API traffic inspection, and zero trust enforcement; endpoint security for developer machines, research environments, browsers, and plugins; data layer controls ensuring proper handling of sensitive data when interacting with AI systems.
• AI Threat Modeling (Enterprise Context) — Develop threat models focused on enterprise AI usage, including risks such as data leakage, prompt injection, model misuse, supply chain risks from AI vendors, and unauthorized agent actions.
• Vendor & Platform Security — Assess and guide secure adoption of third-party AI vendors and platforms, including evaluating data handling practices, model behavior, and integration risks.
• Incident Response for AI Usage — Define and support response approaches for AI-related incidents, such as sensitive data exposure, policy violations, or misuse of AI tools.
• Cross-Functional Technical Leadership — Partner with Legal, Compliance, IT, and Engineering to align AI usage with regulatory requirements, data governance policies, and responsible AI practices.
• Security Enablement — Contribute to internal guidance and education on safe AI usage, including secure prompting, data handling, and appropriate use of AI tools.
• Security Tooling & Implementation — Evaluate and implement tooling for AI security, including AI gateways, DLP integrations, monitoring solutions, and policy enforcement mechanisms.

What You’ll Need to Succeed

• 8+ years of experience in information security, with strong expertise in enterprise, cloud, or application security.
• Hands-on experience designing and implementing security controls in enterprise environments.
• Familiarity with AI/ML systems and how modern AI tools (LLMs, copilots, APIs) are used in practice.
• Experience with cloud platforms (AWS/GCP), SaaS security, and zero trust architectures.
• Experience with data protection technologies (e.g., DLP, data classification, access controls).
• Practical experience with threat modeling, red teaming, or adversarial testing.
• Strong communication and influence skills across technical and non-technical stakeholders.

Bonus Points For

• Experience securing enterprise use of LLMs, copilots, or generative AI platforms.
• Familiarity with AI gateways, prompt filtering, or model interaction controls.
• Experience evaluating or securing third-party AI vendors and APIs.
• Background in regulated environments (biotech, healthcare, defense, or government).
• Experience with browser security, endpoint controls, or SaaS security platforms.
• Knowledge of privacy-enhancing technologies or confidential computing.
• Contributions to AI/ML security research or community.

Your Impact at LILA

The Staff/Principal DevOps Engineer will drive the design, implementation, and optimization of our infrastructure and delivery platforms. This role bridges platform engineering, site reliability, and DevOps practices, building scalable, automated systems that enable fast, reliable software delivery across cloud and Kubernetes environments. You will collaborate with software engineers, lab scientists, and ML engineers to build infrastructure that powers automated scientific analysis, experiment orchestration, and more.

What You'll Be Building

• Build Kubernetes-based infrastructure supporting scientific services, ML pipelines, and platform workloads; including production hardening, RBAC, network policies, and Pod Security Standards
• CI/CD pipelines with GitHub Actions/GitLab CI implementing best practices: build attestations, SBOM generation, dependency scanning, and container image hardening
• Infrastructure-as-code with Terraform and Helm; policy-as-code guardrails (OPA/Kyverno/Checkov) with drift detection
• AWS cloud infrastructure: EKS clusters, IAM least privilege, VPC/PrivateLink networking, KMS/Secrets Manager, ECR, S3, and centralized logging/monitoring
• Platform tooling to streamline deployment, observability, and developer workflows, enabling self-service with secure defaults
• Reliability engineering: SLOs/SLIs, incident response, capacity planning, and performance optimization throughout the stack
• Software supply chain practices: artifact signing, registry governance and vulnerability management
• QA and testing infrastructure: static analysis and code quality gate enforcement in CI pipelines, automated end-to-end and browser-based regression test suites, ephemeral test environments for PR-based validation, and pre-merge quality checks
• Automation and tooling in Python or Go to improve infrastructure operations and integrate telemetry with observability platforms

What You’ll Need to Succeed

• Expertise in DevOps, SRE, or Platform Engineering in large scale cloud environments
• Expertise in deploying to cloud environments (AWS, GCP, etc) using infrastructure-as-code (Terraform, Helm) and containerization
• Deep experience with CI/CD systems (GitHub Actions, GitLab CI, or Jenkins) and GitOps practices
• Strong proficiency in Python/scripting languages for automation and tooling
• Strong understanding of Kubernetes operations: deployments, networking, storage, observability, and troubleshooting

Bonus Points For

• Experience with GitOps tools (ArgoCD, Flux)
• SRE practices: observability platforms, chaos engineering, incident management
• Securing ML/AI pipelines (model registries, training clusters, inference gateways)
• Experience in regulated/audit-heavy environments (SOC 2, ISO 27001)
• Supply chain security maturity: SBOMs, image signing, SLSA concepts
• Administering static analysis platforms (custom quality profiles, security hotspot triage) and scaling browser-based test suites across parallel CI environments
• Prior startup/high-growth experience balancing velocity with reliability

About the Role

Accelerating clinical research is one of the defining challenges in healthcare. Promising therapies exist that patients can't access because the operational infrastructure to run clinical trials efficiently doesn't exist yet. We're building it. That means designing technology systems that bring order to a fragmented landscape of clinical data sources, automating the operational work that slows trials down, and turning real-world clinical data into a foundation for predictive intelligence.

We're building a uniquely valuable data asset: real-world patient and research data flowing across 80+ trial sites, spanning dozens of EHRs and clinical systems, focused on patient populations that are chronically underserved by existing clinical research infrastructure. Your job is to build the pipelines, data models, and AI infrastructure that make this asset real, from ingestion and normalization through to the systems that power predictions on top of it. You'll own data quality and observability as foundational engineering problems. You'll also have a direct hand in shaping how this data drives our AI strategy, what we model, what we predict, and what becomes possible.

This is an opportunity for someone who wants to be part of a small, fast-moving engineering team at a formative stage. You'll shape what gets built, how decisions get made, and what the team becomes.

Responsibilities

• Own the data layer and architecture:  the models, schemas, and infrastructure decisions that everything downstream depends on
• Build and operate the pipelines and transformations that move data from ingestion through normalization, enrichment, and into the formats that support analytics, ML training, and production model serving
• Own data quality and observability: build the systems that make data issues visible and correctable before they compound
• Partner with ML and engineering teams to identify what's modelable, define training data requirements, and build the data foundations for new predictive capabilities
• Define how clinical and operational data is governed across the system
• Evaluate and select the tools and technologies that make up the data stack, with a clear point of view on build vs. buy
• Help shape the engineering culture of a small, growing team: how technical decisions get made, how problems get debated, what rigor looks like in practice

What We’re Looking For

Required Qualifications

• 10+ years of experience in data engineering or related roles, with significant time spent building data systems
• Experience with healthcare data strongly preferred (HL7, FHIR, claims, EHR extracts) or other complex, regulated data domains
• Deep experience modeling and integrating data from multiple heterogeneous sources with inconsistent schemas and quality
• Experience applying AI and LLMs to data engineering problems: extraction, normalization, classification, entity resolution
• Strong understanding of how data infrastructure supports ML workflows from feature engineering to training data pipelines to model serving
• Fluent in SQL and at least one modern programming language (Python, Java, Scala, Go), with experience across modern data infrastructure - distributed processing, streaming, cloud-native storage, orchestration, and transformation frameworks
• Have built data systems from early stages, making foundational decisions with incomplete information
• Naturally raise the quality of the engineering around you through code review, design guidance, and honest technical conversation

Preferred Qualifications

• Experience building data infrastructure that directly supports ML model training and evaluation
• Familiarity with clinical trial operations, EDC systems, or life sciences data
• SOC 2, HIPAA or similar compliance experience baked into engineering practice
• A track record of building or improving data systems that others had given up on making reliable

About the Role

Accelerating clinical research is one of the defining challenges in healthcare. Promising therapies exist that patients can't access because the operational infrastructure to run clinical trials efficiently doesn't exist yet. We're building it. That means designing technology systems that bring order to a fragmented landscape of clinical data sources, automating the operational work that slows trials down, and turning real-world clinical data into a foundation for predictive intelligence.

We're looking for a Staff Software Engineer to own the design and implementation of the core systems that make this possible. This means building robust integrations across a complex, fragmented landscape of EHRs, CTMS platforms, and clinical data sources, each with its own data models, access patterns, and operational constraints. It also means building the data infrastructure that powers our predictive capabilities: the pipelines, feature stores, and training infrastructure that allow us to move from raw clinical data to models that meaningfully improve trial execution. This is a generalist role for someone who thinks in systems. You'll move between architecture and implementation, between integration engineering and ML infrastructure, between defining technical strategy and writing the code that proves it out. The problems are genuinely hard, largely unsolved, and what you build will matter.

This is an opportunity for someone who wants to be a part of a small, fast moving engineering team at a formative stage. You'll shape what gets built, how decisions get made, and what the team becomes.

Responsibilities

• Own the technical architecture for our core systems and build the foundational abstractions and interfaces that everything else is built on top of
• Build reliable integrations with dozens of external clinical data systems (EHRs, CTMS, eSource, labs), treating this as a hard systems design problem, not just an ingestion problem
• Build and evolve the infrastructure that supports model training and predictive capabilities, from ingestion through feature engineering and serving
• Move fast by prototyping to drive experimentation; derisk ideas quickly to keep the team building what works
• Evaluate and choose the technologies we build on: make build vs. buy decisions, select vendors, and shape our long-term infrastructure strategy
• Make the key technical tradeoffs between speed and durability, between generality and shipping
• Work across product, clinical operations, and data science to make sure you're solving the right problems, not just the interesting ones
• Help shape the engineering culture of a small, growing team: how technical decisions get made, how problems get debated, what rigor looks like in practice

What We’re Looking For

Required Qualifications

• Have 10+ years of software engineering experience, with significant time spent designing and building systems not just features
• Experience with healthcare data systems (HL7, FHIR, EHR/EMR integrations) or other highly regulated data environments
• Have 2+ years experience working in a high-growth startup environment
• Have deep experience with system integration, particularly across unreliable or heterogeneous external data sources
• Can think through and explain the full picture of a complex system while still being effective at the implementation level
• Experience using AI tooling and frameworks as part of your engineering workflow
• Have built data pipelines and infrastructure that support analytical or ML workloads in production
• Strong across the backend stack (Python, SQL, cloud infrastructure) and can pick up new tools and systems quickly
• Have built systems from early stages, making foundational decisions with incomplete information, not just extending established infrastructure
• Naturally raise the quality of the engineering around you through code review, architecture guidance, and honest technical conversation

Preferred Qualifications

• Experience building ML training infrastructure or feature platforms
• Familiarity with clinical operations, systems, or life sciences data
• SOC 2, HIPAA or similar compliance experience baked into engineering practice
• A track record of building systems that had to work correctly under real operational constraints, scale and complexity

Overview:

Description:

Minimum Qualifications:

Education:

•  A minimum of a Bachelor's degree is required.

Who We Are

Flagship Pioneering is a biotechnology company that invents and builds platform companies that change the world. We bring together the greatest scientific minds with entrepreneurial company builders and assemble the capital to allow them to take courageous leaps. Those big leaps in human health and sustainability exponentially accelerate scientific progress in areas ranging from cancer detection and treatment to nature-positive agriculture.  

What sets Flagship apart is our ability to advance biotechnology by uniting life science innovation, company creation, and capital investment under one roof in a way that is largely without precedent. Our scientific founders, entrepreneurial leaders, and professional capital managers are each aligned around an institutionalized process that enables us to innovate and transform for the benefit of people and planet.  

Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. 

Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies.

About the Role

The Information Security team has strong detection and response capability and a maturing compliance program. This is a greenfield opportunity to build Flagship’s cloud security and application security engineering practice in earnest — with the CISO and Director of Security Engineering as your strategic partners and a well-resourced program behind you. You’ll define how cloud posture management, SSDLC security, and cloud-side DLP get done at Flagship — in deep partnership with the Infrastructure & Operations team, who are your primary counterparts for cloud architecture, network, and endpoint infrastructure. What makes this role distinctive is the expectation that you’ll build AI-augmented workflows from the start — using LLMs and agentic tooling to handle the routine 80% so your expertise stays focused on the 20% that actually requires human judgment. If you want to own a practice area rather than execute someone else’s playbook, this is that role. You'll own the technical execution of cloud security and AppSec across Flagship and its portfolio, working directly with engineering teams to embed security into their pipelines, not just review them after the fact.

What You'll Own

• Cloud security posture management: own remediation execution against Wiz findings in close partnership with Infrastructure & Operations — building shared remediation playbooks, coordinating finding resolution across AWS environments, and ensuring security controls are implemented consistently with I&O’s infrastructure standards
• CI/CD and SSDLC security: design and implement security guardrails in engineering pipelines — SAST, secrets scanning, IaC security, container scanning — working directly with portfolio engineering teams, and building AI-powered pipeline security automation (e.g., LLM-assisted code review, automated fix suggestions for SAST findings) that reduces developer friction and scales security coverage beyond what manual review allows
• Cloud-side DLP enforcement: build and operationalize data loss prevention controls at the cloud and application layer, not just policy definition
• Cloud identity and access: own technical execution on Entra/Azure AD conditional access, BYOD policy enforcement, and cloud identity governance in partnership with Infrastructure & Operations, who manage the underlying directory and endpoint infrastructure
• Detection engineering (cloud layer): write and tune cloud-side detection rules and contribute to alert fidelity improvements in partnership with the SOC
• AI platform security: contribute to security architecture reviews and guardrail design for AI-powered portfolio products, including Bedrock and EKS-based platforms
• Serve as the embedded security engineering partner for portfolio company engineering teams — not a reviewer at the end of the process, but a collaborator throughout it
• Design and maintain AI-augmented workflows across all functional areas you own — using LLMs, agentic tooling, and automation to multiply your own capacity. You'll be expected to treat AI as a core part of your engineering toolkit, not an experiment: building prompt-driven triage pipelines, automating remediation drafting, and continuously identifying where human judgment is the bottleneck versus where it's being wasted on pattern-matchable work.

What We're Looking For

• 5+ years in cloud security, application security, or a closely related security engineering discipline
• Deep hands-on experience with AWS security services (Security Hub, GuardDuty, IAM, SCPs, CloudTrail) and cloud posture tooling — Wiz experience strongly preferred
• Practical AppSec experience: you've integrated SAST/DAST/SCA tooling into CI/CD pipelines and worked directly with developers to resolve findings, not just filed tickets
• Experience with cloud identity platforms — Entra ID / Azure AD, including conditional access policy design and enforcement
• Ability to write infrastructure-as-code and scripting to automate security controls (Python, Terraform, or equivalent), including comfort working with LLM APIs, prompt engineering, and agentic orchestration frameworks
• Demonstrated experience building AI-augmented security workflows — you've used LLMs, agentic frameworks, or AI-assisted tooling to automate security tasks at scale, not just experimented with ChatGPT. You should be able to articulate which security problems are well-suited to AI automation and which aren't.
• Strong enough communication skills to be credible with engineering leadership and portfolio company CTOs — you’ll be in technical design reviews, not just security reviews Proven ability to build trusted working relationships with Infrastructure & Operations teams — you approach I&O as a partner, not a gatekeeper, and can influence security outcomes through collaboration rather than mandate
• Comfort operating as a self-directed practitioner in a lean team; this role requires you to set your own execution priorities within a defined strategic direction

Nice to Have

• Experience securing ML/AI platforms — Bedrock, SageMaker, or comparable environments
• AWS Security Specialty, GWEB, OSCP, or equivalent certification
• Experience in a portfolio company or multi-entity security model
• Familiarity with HIPAA technical safeguard requirements and PHI data flows in cloud environments
• Experience designing or operating agentic AI workflows for security operations
• Container and Kubernetes security experience (EKS, image scanning, network policy)

Why This Role

This is a net-new capability role on a small team — you won't be executing someone else's existing playbook, you'll be building the cloud and AppSec program from a solid foundation. You’ll work directly with the CISO and collaborate closely with the Director of Security Engineering. Flagship's portfolio spans some of the most technically ambitious biology and AI work happening anywhere, and the security work reflects that complexity. If you want a role where the scope is real, the autonomy is genuine, and you have the freedom to build an AI-augmented security practice — this is it.

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. 

We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship. 

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto. 

#LI-NM1 

The salary range for this role is $148,000 - $203,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Flagship Pioneering currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Flagship Pioneering's good faith estimate as of the date of publication and may be modified in the future.

CMT is looking for a Principal Backend Software Engineer to produce scalable software solutions to reliably collect and manage data from sensors on smartphones and connected devices in vehicles. In this role, you will design architecture and backend infrastructure, and build features and applications that meet the needs of our customers. If you’re interested in using your skills to make the world's roads and drivers safer, we’d like to meet you. The person in this role will own the architecture and evolution of the backend systems that power DriveWell Fusion. You will design and scale high-throughput data pipelines, REST APIs, and real-time event processing systems that handle millions of device connections daily. You will partner with ML and Data Science teams to build the compute and data infrastructure that supports model training, feature engineering, and large-scale inference — including GPU-accelerated workloads. You will drive infrastructure-as-code practices, CI/CD reliability, and system observability to ensure our platform remains performant and resilient as we grow. As a technical leader, you will mentor engineers, set technical direction, and collaborate with product and engineering stakeholders to deliver solutions that keep tens of millions of drivers safe. 

CMT has helped protect over 65 million drivers and prevent over 126,000 crashes worldwide. We build AI to solve some of the most difficult challenges in mobility — understanding and reducing risk, detecting crashes, and getting people life-saving help. The problems are hard. The impact is real. No matter your role, your work will matter at CMT.

Responsibilities: 

• Participate throughout the planning process, collaborating with product managers, data scientists, and fellow engineers to balance technical feasibility with customer needs 
• Use independent judgment and discretion to implement and enhance solutions for telematics insights enabled by our processing pipelines 
• Identify and measure key production performance metrics, ensuring scalability and efficiency
• Design, implement, and maintain automated tests for telematics solutions, ensuring safe delivery of features and fixes 
• Ensure high bar for quality within our sphere of influence 
• Provide expert guidance on cloud software architecture 
• Keep the codebase healthy amidst increasing complexity 
• Mentor junior engineers as needed 
• Complete any additional tasks as they arise 

Qualifications: 

• Bachelor’s degree or equivalent years of experience and/or certification in Computer Science, Engineering, or related field 
• 7+ years of relevant professional experience 
• Proven experience with development at scale 
• Fluency in at least one programming language with ability to learn Python, Go, C++
• Experience with continuous deployment, and test-driven development (TDD) 
• Experience with relational database (RDBMS) schema design 
• Comfortable with AWS or similar services
• EC2, S3, Lambda, SNS, SQS, RDS (Postgres), Dynamo 
• Terraform, Terragrunt 
• Knowledgeable of containerization technologies (specifically Docker) 
• Ability to work independently when needed and to learn quickly

Nice to Haves: 

• Experience with large-scale cloud compute for ML inference, including GPU-accelerated infrastructure (e.g., EC2 GPU instances, SageMaker, EKS with GPU scheduling), GPU vs CPU workload allocation, model serving at scale, and trade-offs between batch and real-time inference 
• Experience building and operating data pipelines (ETL/ELT) at scale, and designing the data infrastructure that ML/Data Science teams rely on for feature engineering, model training, and production inference 
• Hands-on experience designing and operating high-throughput backend systems handling millions of API requests and device connections daily, including real-time data ingestion and event-driven architectures (message queues, streaming platforms) 
• Hands-on experience with containerization (Docker), container orchestration (AWS ECS or Kubernetes), and infrastructure-as-code using Terraform for managing cloud environments at scale
• Proficiency with observability and monitoring (Datadog, CloudWatch) including designing monitors, alerts, and SLOs 
• Strong knowledge in web security, session management, and experience with network diagnostics and analytics tools
• Experience using AI-assisted development tools (e.g., Claude Code, Cursor) as part of daily engineering workflows

Compensation and Benefits: 

• Fair and competitive salary based on skills and experience, and annual performance bonus 
• Equity may be awarded in the form of Restricted Stock Units (RSUs) 
• Medical, Dental, Vision and Life Insurance, matching 401k, short-term & long-term disability and parental leave 
• Unlimited Paid Time Off including vacation, sick days & public holidays 
• Flexible scheduling and work from home policy depending on role and responsibilities

Base Salary Range

• The base salary range for this position is: $167,200 to $209,000. This range is specifically for Cambridge, MA

Additional Perks:

• Work on a mission with real impact: crashes prevented, injuries avoided, lives protected around the world
• Join an industry leader — 65 million drivers protected, powering 140+ programs across 25 countries
• Be part of the team inventing the future of mobility and road safety
• Move fast, own outcomes, do work that matters
• High ownership, small teams, and direct access to leadership — no layers between your work and its impact
• Unlimited PTO, flexible scheduling, competitive salary, annual performance bonus, RSUs, and full benefits including medical, dental, vision, and 401k match
• Summer Fridays
• Join one of our employee resource groups: Black, AAPI, LGBTQIA+, Women, Book Club, and Health & Wellness
• Comprehensive wellness, education, and employee assistance programs

Commitment to Diversity and Inclusion:

At CMT, we believe the best ideas come from a mix of backgrounds and perspectives. 

We are an equal-opportunity employer committed to creating a workplace and culture where everyone feels valued, respected, and empowered to bring their unique talents and perspectives. Diversity is essential to our success, and we actively seek candidates from all backgrounds to join our growing team. 

We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability state. CMT is headquartered in Cambridge, MA. To learn more, visit www.cmtelematics.com and follow us on X @cmtelematics.

About Cambridge Mobile Telematics:

Cambridge Mobile Telematics (CMT) is the world’s largest telematics and AI company for safer mobility. Its mission is to make the world’s roads and drivers safer. The company’s AI-driven platform, DriveWell Fusion®, proactively identifies and reduces driving risk, leading to fewer crashes and injuries. To date, CMT’s technology has helped prevent over 126,000 crashes worldwide. CMT enables partners to measure risk, detect crashes, provide life-saving assistance, and streamline claims. Headquartered in Cambridge, MA, CMT operates globally with offices in Budapest, Hungary; Chennai, India; Seattle, Washington; Tokyo, Japan; and Zagreb, Croatia. Learn more at www.cmt.ai.

Philo: a streaming service for TV and movie lovers

At Philo, we're a group of technology and product people who set out to build the future of television, marrying the best in modern technology with the most compelling medium ever invented — in short, we're building the TV experience that we've always wanted for ourselves. In practice this means leveraging cloud delivery, modern tech stacks, machine learning, and hand-crafted native app experiences on all of our platforms. We aim to deliver a rock solid experience on the streaming basics, while cooking up next generation multi-screen and multi-user playback experiences.

Data at Philo

Data underpins everything we do at Philo: making informed business decisions; analyzing and improving the quality of our streaming experience; running product experiments to optimize our signup flows and improve user journeys; and making it effortless for our users to find the perfect thing to watch. Philo serves over a billion streams to its users every year, generating a wealth of data that we leverage at all levels of the organization. Philo's data platform operates at a very large scale, processing trillions of events annually in a petabyte-scale data lake and supporting thousands of data workflows and analytical queries that power decision-making across the company.

Philo's Data Engineering team encompasses both data engineering and analytics engineering. As an analytics engineer at Philo, you'll own the data modeling layer that turns raw event and application data into the clean, trusted data products the entire company relies on — from metric definitions and dimensional models to the governed semantic layer that ensures everyone is looking at the same numbers. You'll work closely with data scientists, analysts, and business stakeholders across the organization to understand their analytical needs and translate them into well-modeled, well-documented, and performant data products in dbt and Snowflake.

We are passionate about providing a high-quality, trustworthy data platform for the entire company, using both cutting-edge technologies and proven engineering practices in close collaboration with every department. Our analytics engineering stack centers on dbt and Snowflake, supported by tools like Segment, Avo, and BigEye for event tracking, data quality, and observability.

Some of the recent projects that analytics engineers at Philo have worked on include building new models for key financial data, dbt model design and refactoring, metric definition and governance, per-query cost optimization in Snowflake, and developing data quality testing and documentation frameworks.

The Role

We're looking for a Senior Analytics Engineer to own and elevate the data modeling layer that powers decision-making across Philo. In this role, you'll be the person who transforms raw, messy application and event data into clean, trusted, well-documented data products that the entire company relies on. You'll design and maintain dimensional models, define and govern key business metrics, and ensure semantic consistency across our data stack — so that when someone asks "what does this number mean?", there's always a clear, reliable answer.

This is a high-impact IC role: you'll partner directly with stakeholders across Finance, Product, Marketing, Ad Sales, and Engineering to deeply understand their analytical needs and translate them into scalable, performant dbt models and data products. You'll also work closely with the data engineering side of the team to ensure the underlying infrastructure supports your modeling work, and with analysts and data scientists to make sure the data you deliver is easy to use, well-tested, and trustworthy.

The ideal candidate has strong opinions about how analytics engineering should be done — how to structure a dbt project, when to denormalize, how to manage slowly changing dimensions, how to build a metric layer that people actually trust — and the experience to back those opinions up.

Responsibilities:

• Design, build, and maintain Philo's core dimensional models and data marts in dbt, serving as an owner of the analytics engineering layer of our data stack
• Define and govern key business metrics and KPIs, ensuring consistent definitions and reliable calculations across all downstream reporting and analytics
• Partner with stakeholders across the organization (Finance, Product, Marketing, Ad Sales, Content, and others) to understand their data needs and translate business questions into well-modeled, performant data products
• Establish and enforce best practices for dbt project structure, model design patterns, documentation, and testing — raising the quality bar for analytics engineering at Philo
• Build and maintain comprehensive data documentation and a data catalog so that analysts, data scientists, and business users can confidently self-serve
• Implement and maintain data quality checks and monitoring (e.g., via dbt tests, BigEye, or similar tools) to proactively catch issues before they reach stakeholders
• Optimize query performance and warehouse cost efficiency in Snowflake through thoughtful model design, materialization strategies, and incremental processing patterns
• Collaborate with data engineers on pipeline design and data ingestion to ensure raw data lands in forms that support clean, efficient downstream modeling
• Drive alignment across teams on data definitions, naming conventions, and a single source of truth — building stakeholder trust in data and reporting over time
• Contribute to the evolution of Philo's overall data platform strategy, particularly as it relates to the semantic/metric layer, data governance, and analytics engineering tooling

Key Qualifications:

• 8+ years of professional experience in analytics engineering, data modeling, or a closely related role, with significant hands-on experience building and maintaining production dbt projects or a similar data transformation tool
• Deep expertise in SQL and dbt, including advanced model design patterns (dimensional modeling, incremental models, slowly changing dimensions, and snapshot strategies)
• Experience developing in a BI tool that leverages semantic layers, such as Mode, Looker, Omni, SSAS Cubes, or similar
• Strong experience with Snowflake or a comparable cloud data warehouse, including performance tuning and cost optimization
• Proven ability to translate ambiguous business questions into clean, well-structured data models that stakeholders trust and rely on
• Experience defining, governing, and maintaining business metrics and KPIs across an organization
• Strong communication skills — you can explain data modeling decisions to a VP of Finance just as clearly as to a fellow engineer
• A strong sense of ownership and quality: you care deeply about data accuracy, documentation, testing, and making the data stack better over time
• Experience working with data quality and observability tools (e.g., BigEye, Elementary, dbt tests, Great Expectations, or similar)

Ideal Qualifications:

• Experience in the media, streaming, or entertainment industry, with familiarity with video delivery analytics, content performance metrics, or advertising data
• Familiarity with event tracking design and tools like Segment or Avo
• Experience with Apache Iceberg, Spark, or other large-scale data processing frameworks
• Familiarity with data governance frameworks and building organizational alignment around a single source of truth
• Experience mentoring junior analytics engineers or analysts

More about Philo

At Philo, we're a company that puts people first—both our subscribers and our team. We empower our colleagues to do their best work while supporting one another in pursuing shared goals. We value pragmatism, pride in our work, and passion, with transparency and openness as fundamental parts of our culture.

We're committed to diversity, equity, inclusion, and accessibility as we grow the Philo team and shape the future of TV. We believe that a diverse range of voices and perspectives enables us to innovate faster and create the best experiences for our subscribers. Philo is proud to be an Equal Opportunity Employer. We're committed to supporting every candidate and employee. If you need an accommodation at any stage of the process, please email recruiting@philo.com and we'll work with you to meet your needs.

Philo offers 70+ top-rated networks streaming live and on-demand, including AMC, BET, CMT, Comedy Central, Discovery Channel, Food Network, Hallmark Channel, HGTV, HISTORY, Investigation Discovery, Lifetime, MTV, Nickelodeon, OWN, VH1, We TV, and more. It also includes all the groundbreaking originals and blockbuster movies available with AMC+ and access to HBO Max Basic With Ads and discovery+. Our extensive library boasts over 85,000 titles, and our unlimited DVR allows users to save their favorite shows and movies for up to a year, skipping ads for a seamless viewing experience. Stream on up to three devices simultaneously, whether on your phone, tablet, laptop, or TV using Roku, Apple TV, Fire TV, Samsung TV, Android TV, Vizio TV, or Chromecast.

Philo is headquartered in San Francisco, with offices in New York City and Cambridge, MA. Our leadership team includes alums from HBO, Tubi, and Meraki, and is backed by NEA and industry partners like Warner Brothers Discovery, Viacom, AMC, and A&E.

Join us at Philo and be part of a team that's shaping the future of TV!

Status: Full-time
Location: San Francisco, CA, Brooklyn, NY, Cambridge, MA, or remote within the U.S.
Compensation: Includes annual salary, company stock options, and health benefits. Salary is determined by experience and location:

• San Francisco, New York City: $170K - $205K
• Boston, DC Metro, Los Angeles, Seattle: $160K - $195K
• Denver, Atlanta, Austin, Las Vegas, Sacramento, Chicago: $155K - $185K
• Texas, Florida: $145K - $175K

We value a diverse and inclusive workplace and we welcome people of different backgrounds, experiences, skills, and perspectives. Philo is an equal opportunity employer. We believe that everyone does their best work when they are supported by each other and the company, and we offer a generous set of benefits to make sure the Philo team is happy and healthy. Here is a sampling of the benefits we offer our team:

• Full health, dental and vision coverage for you and your family
• 401(k) plan with employer contributions (we match 100% of deferrals up to 3% of pay and 50% of the next 2% of pay)
• Flexible working hours
• Up to 20 weeks of fully paid parental leave
• Unlimited paid time off for vacation and sick leave
• $2,000 annual vacation bonus (we pay you to take a two week vacation)
• $5,250 annually for professional development and educational assistance
• $1,250 annual home office + TV stipend during first year of employment ($250 annually thereafter)
• $500/month ($6,000/year) bonus for employees who commit to working at least 3 days per week in our offices, plus generous commuter benefits ($315/month towards transit, rideshare, bike rental, or parking at our HQ office in San Francisco)
• Free Gympass subscription — an all-in-one corporate benefit that gives employees the largest selection of gyms, studios, classes, training and wellness apps
• Dog-friendly office
• And much more!

For California Residents: Philo's CCPA Notice at Collection – Employees, Applicants, Owners, Directors, Officers and Contractors

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

About Philo

Philo is building the future of television. Our product lets you watch your favorite shows on all the devices you care about, with seamless playback, insightful discovery, and effortless sharing. In short, we’re building the TV experience that we’ve always wanted for ourselves.

We’re a company that puts people first — both our subscribers and our team. At Philo, our philosophy is to empower our colleagues to do their best work while supporting each other in pursuing shared goals. We value pragmatism, pride in our work, and passion. We believe in having transparency and openness across all parts of the company.

We are committed to diversity and inclusion as we grow the Philo team and shape the future of TV. We believe that a diverse set of voices and perspectives on our team enables us to innovate faster and create the best experience for our subscribers.

Philo is headquartered in San Francisco, with offices in New York City and Cambridge, MA. Our leadership team includes alums from HBO, Tubi, and Meraki, and is backed by NEA and industry partners like Warner Brothers Discovery, Viacom, AMC, and A&E.

Lead Backend Software Engineer (Product)

Philo aims to connect customers with their favorite shows, help them discover new favorites, and get them seamlessly into the video player watching their next shows. The Product API team is central to this mission and powers virtually every non-media interaction in our application delivering a personalized experience for millions of users across web, mobile, and connected TV platforms.

The team builds out the Philo show catalog and exposes it via search, ML powered recommendation, and platform integration like search on Roku, FireTV, and tvOS. They provide a robust API to clients platforms to access this catalog along with features needed for a streaming service like saving shows, sending notifications, and running experiments. They do this all while load testing and scaling the system to millions of users and considering security and privacy. A challenge for the team is to support many different clients and the team has built out frameworks, infrastructure, and APIs to enable this. For example, building out a framework on top of GraphQL to dynamically change the home page instantly and across all platforms without any client modification allowing for content curation, user personalization, and all types of home page experimentation.

Engineering leads at Philo lead by example, and are expected to ship features, triage bugs, manage releases, and generally advocate for quality throughout the codebase. We are seeking an enthusiastic, experienced backend engineer with a deep technical background building scalable APIs, services, and platform infrastructure. You will contribute to the technical vision and roadmap for Product API, drive architecture and reliability with strong observability, coordinate cross-team delivery to unblock new user experiences, and ensure partner integrations land smoothly. You'll model best practices to the team, unblock your teammates when they are stuck, and help ensure platform stability and clarity of contracts as the team delivers multi-quarter outcomes.

Responsibilities

• Provide technical leadership to members of the Product API team, including input on system architecture and design tradeoffs, as well as coaching other members of the team and mentoring new hires.
• Collaborate with product and client engineering teams to design and deliver GraphQL APIs that enable rich, performant user experiences while maintaining clean separation of concerns and optimal client-server interactions.
• Own and evolve critical product subsystems including recommendations, catalog, search, in-app notifications, user preferences, viewing history, collections, experiments, and feature flags.
• Build and maintain proxy and augmentation layers that integrate domain services from across the organization (such as video infrastructure, recommendations systems, and search) into a cohesive, unified API.
• Drive continuous improvements to the reliability, performance, scalability, and maintainability of Philo's product API infrastructure, ensuring sub-second response times and high availability across all endpoints.
• Collaborate with data science and product analytics teams to instrument the API layer for experimentation, A/B testing, and feature rollouts, enabling data-driven product decisions.
• Build and enhance observability tools to proactively monitor API performance, identify bottlenecks, debug issues, and ensure optimal cache utilization across the system.
• Work with infrastructure teams to optimize database queries, implement effective caching strategies, and ensure DataServer scales efficiently as Philo's user base grows.

Qualifications

• 8+ years of software development experience.
• 2+ years of experience mentoring and providing technical guidance to other engineers (bonus points for experience or interest in managing engineering teams).
• Strong experience designing and implementing GraphQL APIs at scale (bonus points for experience with complex schema design, query optimization, and federation patterns).
• Proven track record of building highly efficient and highly available backend services using NodeJS, Ruby, Golang, Python, or similar programming languages.
• Experience operating in cloud computing environments using modern software deployment technologies (e.g. Docker, Kubernetes, AWS).
• Deep understanding of API design principles, RESTful and GraphQL patterns, caching strategies, and performance optimization techniques.
• Experience working with large amounts of data and making data-based decisions to prioritize projects, including familiarity with relational and non-relational databases and modern data warehousing and querying with SQL.
• Strong systems thinking with the ability to design cohesive API abstractions that cleanly separate concerns while enabling flexibility for diverse client needs.
• Experience building proxy and aggregation layers that integrate multiple backend services into unified APIs.
• Familiarity with experimentation frameworks, feature flag systems, and A/B testing infrastructure.
• Experience and aptitude for collaborating and communicating with internal stakeholders across product, design, client platform engineering, and data science teams.
• Understanding of video streaming product ecosystems and the unique challenges of building APIs for multi-platform applications (web, mobile, TV).
• Expertise in either product-facing API development or machine learning systems and model serving infrastructure.

We are language agnostic, but most of our backend code is written in Golang, NodeJS and Ruby, with some C++ and Python. Our services run on Kubernetes, and we practice continuous deployment across all of our systems.

More about Philo

At Philo, we’re a company that puts people first—both our subscribers and our team. We empower our colleagues to do their best work while supporting one another in pursuing shared goals. We value pragmatism, pride in our work, and passion, with transparency and openness as fundamental parts of our culture.

We’re committed to diversity, equity, inclusion, and accessibility as we grow the Philo team and shape the future of TV. We believe that a diverse range of voices and perspectives enables us to innovate faster and create the best experiences for our subscribers. Philo is proud to be an Equal Opportunity Employer. We’re committed to supporting every candidate and employee. If you need an accommodation at any stage of the process, please email recruiting@philo.com and we’ll work with you to meet your needs.

Philo offers 70+ top-rated networks, including AMC, BET, CMT, Comedy Central, Discovery Channel, Food Network, Hallmark Channel, HGTV, HISTORY, Investigation Discovery, Lifetime, MTV, Nickelodeon, OWN, VH1, We TV, and more. It also includes all the groundbreaking originals and blockbuster movies available with AMC+ and access to HBO Max Basic With Ads and discovery+. Our service also includes 100+ free channels and premium add-ons like STARZ and MGM+.

Our extensive library boasts over 85,000 titles, and our unlimited DVR allows users to save their favorite shows and movies for up to a year, skipping ads for a seamless viewing experience. Stream on up to three devices simultaneously, whether on your phone, tablet, laptop, or TV using Roku, Apple TV, Fire TV, Samsung TV, Android TV, Vizio TV, or Chromecast.

Join us at Philo and be part of a team that's shaping the future of TV!

Projected Start Date: ASAP
Status: Full-time
Location: San Francisco, CA, Brooklyn, NY, Cambridge, MA, or remote within the U.S.
Compensation: Includes annual salary, company stock options, and health benefits. Salary is determined by experience and location:

• San Francisco, New York City: $200K - $235K
• Boston, DC Metro, Los Angeles, Seattle: $190K - $225K
• Denver, Atlanta, Austin, Las Vegas, Sacramento, Chicago: $180K - $215K
• Texas, Florida: $170K - $205K

We value a diverse and inclusive workplace and we welcome people of different backgrounds, experiences, skills, and perspectives. Philo is an equal opportunity employer. We believe that everyone does their best work when they are supported by each other and the company, and we offer a generous set of benefits to make sure the Philo team is happy and healthy. Here is a sampling of the benefits we offer our team:

• Full health, dental and vision coverage for you and your family
• 401(k) plan with employer contributions (we match 100% of deferrals up to 3% of pay and 50% of the next 2% of pay)
• Flexible working hours
• Up to 20 weeks of fully paid parental leave
• Unlimited paid time off for vacation and sick leave
• $2,000 annual vacation bonus (we pay you to take a two week vacation)
• $5,250 annually for professional development and educational assistance
• $1,250 annual home office + TV stipend during first year of employment ($250 annually thereafter)
• $500/month ($6,000/year) bonus for employees who commit to working at least 3 days per week in our offices, plus generous commuter benefits ($315/month towards transit, rideshare, bike rental, or parking at our HQ office in San Francisco)
• Free Gympass subscription — an all-in-one corporate benefit that gives employees the largest selection of gyms, studios, classes, training and wellness apps
• Dog-friendly office
• And much more!

For California Residents: Philo’s CCPA Notice at Collection – Employees, Applicants, Owners, Directors, Officers and Contractors

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

We are seeking an experienced Embedded Software Engineer (Rust) to join our Platform team (folks looking after the spacecraft). The successful candidate will play a crucial role in developing software for our satellite systems, contributing to the expansion and enhancement of our space-based data collection capabilities.

Ideal candidates will embrace the commercialization of nanosatellite systems and adapt to low-cost, fast-paced systems design, development, and implementation methodologies that set Spire apart from our competition. In this fast-paced environment, the design to launch cycle is measured in weeks and months, not years!

What You’ll Do as a Spacecraft Embedded Software Engineer:

• Develop daemons in Rust that interface with embedded systems using low- level protocols
• Implement communication interfaces between embedded systems and higher-level processes
• Integrate C code for specific hardware interfaces
• Contribute to the design and implementation of fault-tolerant systems
• Collaborate closely with the Electrical Engineering team to ensure optimal software-hardware integration
• Create and maintain comprehensive documentation for APIs and system architectures
• Contribute to the continuous improvement of our development processes and tools

Key Skills:

• Proven experience in embedded systems development using Rust
• Knowledge of or adaptability to Linux-based development (Ubuntu) 
• Proficiency in integrating C code with Rust projects
• Experience with real-time communication protocols
• Experience with inter-process communication protocols
• Understanding of electronics and ability to communicate effectively with hardware engineers
• Excellent documentation skills

Preferred Skills: 

• Familiarity with safety-critical embedded systems in any industry
• Experience with Yocto for embedded systems
• Knowledge of version control systems, particularly Git and GitHub
• Familiarity with CI/CD pipelines
• Experience with project management tools
• Proficiency in scripting languages like Python and Bash
• Understanding of cybersecurity principles for embedded systems
• Knowledge of telemetry and command systems
• Experience with formal verification methods for critical software components
• Experience in implementing Fault Detection, Isolation, and Recovery (FDIR) systems for embedded applications

Tools and Technologies: Rust, C | Scripting languages (Bash/Python) | Ubuntu (development environment)  | Yocto (target environment) | Version control using Git

Spire operates a hybrid work model, and this position will require you to work a minimum of three days per week in the office.

Access to US export-controlled software and/or technology may be required for this role. If needed, Spire will arrange the necessary licenses—this is not something candidates need to have before applying. #LI-RK1

We are seeking an experienced Embedded Software Engineer (Rust) to join our Platform team (folks looking after the spacecraft). The successful candidate will play a crucial role in developing software for our satellite systems, contributing to the expansion and enhancement of our space-based data collection capabilities.

Ideal candidates will embrace the commercialization of nanosatellite systems and adapt to low-cost, fast-paced systems design, development, and implementation methodologies that set Spire apart from our competition. In this fast-paced environment, the design to launch cycle is measured in weeks and months, not years!

What You’ll Do as a Spacecraft Embedded Software Engineer:

• Develop daemons in Rust that interface with embedded systems using low- level protocols
• Implement communication interfaces between embedded systems and higher-level processes
• Integrate C code for specific hardware interfaces
• Contribute to the design and implementation of fault-tolerant systems
• Collaborate closely with the Electrical Engineering team to ensure optimal software-hardware integration
• Create and maintain comprehensive documentation for APIs and system architectures
• Contribute to the continuous improvement of our development processes and tools

Key Skills:

• Proven experience in embedded systems development using Rust
• Knowledge of or adaptability to Linux-based development (Ubuntu) 
• Proficiency in integrating C code with Rust projects
• Experience with real-time communication protocols
• Experience with inter-process communication protocols
• Understanding of electronics and ability to communicate effectively with hardware engineers
• Excellent documentation skills

Preferred Skills: 

• Familiarity with safety-critical embedded systems in any industry
• Experience with Yocto for embedded systems
• Knowledge of version control systems, particularly Git and GitHub
• Familiarity with CI/CD pipelines
• Experience with project management tools
• Proficiency in scripting languages like Python and Bash
• Understanding of cybersecurity principles for embedded systems
• Knowledge of telemetry and command systems
• Experience with formal verification methods for critical software components
• Experience in implementing Fault Detection, Isolation, and Recovery (FDIR) systems for embedded applications

Tools and Technologies: Rust, C | Scripting languages (Bash/Python) | Ubuntu (development environment)  | Yocto (target environment) | Version control using Git

Spire operates a hybrid work model, and this position will require you to work a minimum of three days per week in the office.

Access to US export-controlled software and/or technology may be required for this role. If needed, Spire will arrange the necessary licenses—this is not something candidates need to have before applying. #LI-RK1

We are seeking an experienced Embedded Software Engineer to join our Platform team supporting Spacecraft Operations. The successful candidate will play a crucial role in supporting other disciplines by focusing on the embedded software aspects of our satellite systems. The Platform team interfaces directly with many engineering groups to conduct R&D, design, manufacturing, and operations activities, ultimately ensuring all current and future spacecraft systems satisfy their mission.

Ideal candidates will embrace the commercialization of nanosatellite systems and adapt to low-cost, fast-paced systems design, development, and implementation methodologies that set Spire apart from our competition. In this fast-paced environment, the design to launch cycle is measured in weeks and months, not years!

What You’ll Do as a Senior Embedded Software Engineer:

• Design, implement and test, deploy and maintain embedded firmware
• Collaborate with other engineering functions on scoping, architecture and system design
• Resolve on-orbit and on-ground issues related to embedded systems
• Implement, optimize and maintain various serial protocols
• Design and develop interface tools to improve abstraction between the embedded system and other satellite components 
• Debug and resolve complex embedded systems issues in a timely manner
• Write and maintain technical documentation

Key Skills: 

• Bachelor's degree in Computer Science, Electrical Engineering, or related field
• Mastery of Embedded C programming language
• Proficiency with scripting languages like Python and Bash
• Extensive experience with real-time operating systems (RTOS), specifically FreeRTOS
• Familiarity with serial protocols and implementations
• Strong problem-solving skills, particularly in debugging embedded systems
• Experience with version control systems (e.g., Git)
• Experience developing on Linux (Ubuntu)
• A base level of mathematical knowledge (engineering mathematic or similar)
• Excellent communication and teamwork abilities

Preferred Skills: 

• Experience with space systems or satellite technology
• Familiarity working to coding standards and using static analysis tools
• Experience writing Rust for resource constrained environments (embedded Linux)
• Experience with embedded Linux
• Knowledge of control systems and algorithms

Tools and Technologies:

• FreeRTOS for real-time operating system implementation
• GNU ARM Embedded Toolchain for code compilation
• GDB for debugging, complemented by extensive use of serial and/or CAN debugging
• Experience with debugging techniques for systems without JTAG access, particularly for remote issue resolution
• Familiarity with manual testing procedures for embedded interface code
• Experience working with Arm Cortex Microcontrollers
• Version control using Git

Spire operates a hybrid work model, and this position will require you to work a minimum of three days per week in the office.

Access to US export-controlled software and/or technology may be required for this role. If needed, Spire will arrange the necessary licenses—this is not something candidates need to have before applying. #LI-RK1